the influences of company size, audit quality, audit...
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THE INFLUENCES OF COMPANY SIZE, AUDIT QUALITY, AUDIT
TENURE, AND AUDIT PRICING TO THE GOING CONCERN AUDIT
OPINION (GCAO)
(Empirical Studies to Property Companies that Listed in Indonesian Stock
Exchange Period 2013-2015)
By :
Delia Dwi Ganysa
1110082100013
ACCOUNTING INTERNATIONAL DEPARTMENT
FACULTY OF ECONOMICS AND BUSINESS
SYARIF HIDAYATULLAH STATE ISLAMIC UNIVERSITY JAKARTA
2017
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CURRICULUM VITAE
PERSONAL DETAIL
Name : Delia Dwi Ganysa
Place of Birth : Cimahi
Date of Birth : December, 29th
1993
Gender : Female
Religion : Islam
Marital Status : Single
Address : Perumnas Adiarsa, Jln. Cisokan Raya No.153, Karawang
Phone : +62813 1516 6937
Email : [email protected]
FORMAL EDUCATION
Elementary School : SDN Adiarsa 3 Karawang
Intermediate : SMPN 1 Karawang
High School : SMAN 1 Karawang
College : Jakarta Islamic State University
NON-FORMAL EDUCATION
English Course : LIA Jakarta (Toefl Class)
Study Trip : 1. Study Trip to Germany 2012 with HAW University
International Conflict Management
2. Workshop at Rostock University
3. Workshop at Inholland University, Holland
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ORGANIZATIONAL AND COMMITTEE EXPERIENCES
Member of Badan Eksekutif Mahasiswa Fakultas Ekonomi Period 2011-2012
Seminar “Proposal and Management Organization”
Seminar “Building Leadership”
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THE INFLUENCES OF COMPANY SIZE, AUDIT QUALITY, AUDIT
TENURE, AND AUDIT PRICING TO THE GOING CONCERN AUDIT
OPINION
ABSTRACT
The purpose of this research was to analyze the influence of company size,
audit quality, audit tenure, and audit pricing to the going concern audit opinion
that accepted by companies in property industry.
Sampling method used logistic regression. This research used property
industry and real estate which were listed in Indonesia Stock Exchange during
2013-2015. The number of property industry and real estate in this research were
21 companies with 3 years observation.
Result showed that company size, audit quality, audit tenure, audit pricing
are infulences to the going concern audit opinion.
Keyword: Company Size, Audit Quality, Audit Tenure, Audit Pricing, Going
Concern.
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PENGARUH UKURAN PERUSAHAAN, KUALITAS AUDIT, MASA
KERJA AUDIT, DAN BIAYA AUDIT TERHADAP GOING CONCERN
ABSTRAK
Penelitian ini bertujuan untuk menganalisis pengaruh ukuran perusahaan,
kualitas audit, masa kerja audit, dan biaya audit terhadap keberlangsungan
perusahaan going concern.
Metode pengambilan sampel yang digunakan adalah regresi logistik. Penelitian
ini menggunakan sampel industri properti dan real estate yang terdaftar di Bursa
Efek Indonesia selama 2013-2015. Jumlah industri properti dan real estate dalam
penelitian ini adalah 21 perusahaan selama 3 tahun pengamatan.
Hasil penelitian menunjukan bahwa ukuran perusahaan, kualitas audit, masa
kerja audit, biaya audit berpengaruh terhadap keberlangsungan perusahaan.
Kata kunci: Ukuran Perusahaan, Kualitas Audit, Masa Kerja Audit, Biaya
Audit, Keberlangsungan Perusahaan
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FOREWORD
Assalamualaikum Wr. Wb.
All praises to Allah SWT, the Most Gracious and the Most Merciful, the
Cherisher and Sustainer of the worlds; who always give the writer all the best of
this life and there is no doubt about it. Shalawat and Salaam to the Prophet
Muhammad SAW and his family. With blessing and mercy from Allah SWT, the
writer can complete this thesis to fulfill one of the requirements in accomplishing
bachelor degree.
The writer is also well-aware that without advice and support from various
parties, this thesis will not be realized properly. Therefore, the writer would like to
take her opportunity to express her deep and sincere gratitude to the following:
1. Parents, papa Drs.Yoeyoes Sujana, MM. and mom Siti Juhaeriah Eka,
brother, Reza Aditya, Adm. that always give me strength and support.
2. Dean Faculty of Economics and Business Dr. M. Arief Mufraini, Lc., M.Si
3. Yessi Fitri, SE.,M.Si.,Ak.,CA. as Head of Accounting Department.
4. Supervisor, Hepi Prayudiawan,SE.,MM.,Ak.,CA thanks for your
willingness to be my supervisor that always teach and share your
knowledge, also teach me patiently.
5. All lectures that teach me along this period that always share knowledges,
educate us patiently, improve our manner.
6. Accounting international 2010, suci, nunu, detri, fadly, reza, abdil, rika,
saddam, halim.
7. Management international 2010, anisa, rizma, monica, sayyid, baong, elfa.
All international students that always supports, thank you so much.
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8. My best friend siska, anindya, meyga, emma, sobari, fadly, you guys
always remind about my prority to hurry on doing my thesis. Thanks a lot
for the support.
9. FEB staff, kak sugih, kak bonyx, thank you for provides direction about
thesis and the advice. It helps me a lot.
10. All people that keep asking, “When will you graduate?” or “Oh, I thought
you already graduated” or “I thought you already work” to me every time
when they saw me. Thanks for the questions that make me highly
motivated to catch the thesis deadline.
The writer realized that this thesis is still far from perfection due to limited
knowledge of the writer. All the suggestions and constructive criticsm are
welcomed in order to make this thesis better. Hope, this thesis will be useful
for any researcher or reader.
Wassalamualaikum Wr. Wb.
Jakarta, July 2017
Delia Dwi Ganysa
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TABLE OF CONTENTS
Cover ..................................................................................................................... i
Thesis Approval Sheet ........................................................................................... ii
Comprehensive Examination Approval Sheet ....................................................... iii
Thesis Examination Approval Sheet ..................................................................... iv
Authenticity Scientific Sheet ................................................................................. v
Curriculum Vitae ................................................................................................... vi
Abstract.................................................................................................................. viii
Abstrak .................................................................................................................. ix
Foreword................................................................................................................ x
Table of Content .................................................................................................... xii
List of Tables ......................................................................................................... xv
List of Figures........................................................................................................ xvi
TABLE OF CONTENTS ......................................................................................
CHAPTER I INTRODUCTION ........................................................................... 1
A. Background .............................................................................. 1
B. Problem Formulation ................................................................ 12
C. Research Objectives and Benefits ............................................. 12
CHAPTER II LITERATURE REVIEW ............................................................... 16
A. Grand Theory ............................................................................ 16
1. Agency Theory ................................................................... 16
2. Going Concern ................................................................... 19
3. Auditors Responsibility to Going Concern ........................ 19
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4. Audit Going Concern Opinion ........................................... 20
5. Company Size .................................................................... 22
6. Audit Quality...................................................................... 23
7. Audit Tenure ...................................................................... 25
8. Audit Pricing ...................................................................... 27
B. Previous Research ..................................................................... 28
C. Logical framework and Hypothesis .......................................... 29
1. Company Size to Going Concern Audit Opinion .............. 29
2. Audit Quality to Going Concern Audit Opinion ................ 30
3. Audit Tenure to Going Concern Audit Opinion ................ 31
4. Audit Pricing to Going Concern Audit Opinion ................ 32
CHAPTER III Research Methoodology ................................................................ 34
A. Research Scope ......................................................................... 34
B. Sampling Method ...................................................................... 34
C. Data Collection Method ............................................................ 35
D. Analysis Methods ...................................................................... 35
1. Hypotheses Testing ............................................................ 35
2. Assess the Feasibility of Regression Model ...................... 36
3. Assessing Model Overall (Overall Model Fit Test) ........... 37
4. Coefficient Determination (R2) ......................................... 37
5. Classification Table............................................................ 38
6. Descriptive Statstics ........................................................... 38
6. Method of Logistic Regression .......................................... 38
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E. Optimalization of Variable ........................................................ 39
1. Company Size (X1) ............................................................ .39
2. Audit Quality (X2) ............................................................. 39
3. Audit Tenure (X3) .............................................................. 40
4. Audit Pricing (X4) ............................................................. 40
CHAPTER IV RESEARCH AND FINDINGS .................................................... 42
A. Descriptive Statistic Analysis ................................................... .42
1. Test Before Independent Variables ....................................... 43
2. Model Feasibility Test (Goodness of Fit) ............................. 45
B. Test Hosmer and Lemeshow ..................................................... 46
C. Overall Model Testing (Overall Model Fit) .............................. 47
1. Chi Square ............................................................................. 47
2. Cox and Snell‟s R Square and Negelkerke‟s R Score........... 50
D. Classification Test 2 X 2 ........................................................... .51
E. Hypothesis Test ......................................................................... .52
CHAPTER V CONCLUSION AND RECOMMENDATION ............................. 56
A. Conclusion ................................................................................ 56
B. Recommendation....................................................................... 56
REFERENCES ...................................................................................................... 58
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LIST OF TABLES
2.1 Previous Research Table .............................................................................. 28
3.1 Variable Operationalization .......................................................................... 41
4.1 Descriptive Table.......................................................................................... 42
4.2 Classification Table ...................................................................................... 44
4.3 Variable in The Equation.............................................................................. 44
4.4 Variable not in the Equation ......................................................................... 45
4.5 Hosmer and Lemeshow Test ........................................................................ 47
4.6 Itteration History .......................................................................................... 48
4.7 Itteration History .......................................................................................... 49
4.8 Omnimbus Test ............................................................................................ 49
4.9 Model Summary .......................................................................................... 50
4.10 Classification Table .................................................................................... 51
4.11 Classification Table .................................................................................... 53
APENDIXES ...................................................................................................... 61
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LIST OF FIGURES
2.1 Logical Framework ...................................................................................... 33
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Chapter I
Introduction
A. Background
Global economics development, improvements of purchase power investors,
and inaccurate performances on financial statements company, becomes a
phenomenon that being concerns for business executant and auditor. The
investments on money market potentially results income for business executants.
Investors have to know company financial condition first before invest the shares.
Through management performances, internal audit, transparancy, and company
ability to pay the debt, that means company was save for invested.
The company that declare as a going concern, but for years later collapse,
that might be something wrong on auditor opinion or lack of management
performances. Going Concern always connected with management ability at entity.
Investors consideration is depend on auditor opinion about an entity. It means
auditor become intermediaries between investors and entity (Achwaludin, Novaz
2011). Fraudulent issues, incompetent management ability on handling financial
statements, and assymetric information, becomes main points of collapsed
company. Nowadays, financial statement of company have to present fairly as a
real financial condition of company. Financial statements have to present business
and finance information that accurate and appropriate with IFRS.
(Louwers J. Timothy,et.al, 2007) Financial reporting is to provide
statements of financial position (balance sheets), results of operations (income
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statements), changes in cash flows (statements of cash flows), and accompanying
disclosures (footnotes) to outside decision makers who do not have access to
management‟s internal sources of information. A company‟s accountants under the
direction of this function. Thus, the financial statement contain management‟s
assertions about transactions and events that occured during the period being
audited (primarily the income statement and statement of cash flows), assertions
about account balances at the end of period (primarly the balance sheet), and
assertions about financial statement presentation and disclosure (primarly the
footnote disclosure).
Financial statements is the report that present financial information that can
be used as a media shows reliable financial flow that can justified to public, and
appropriate with company real conditions. The financial statements, including the
footnotes accompanying the financial statements, are the responsibility of
management, although auditors frequently draft them (Louwers J. Timothy, 2007).
Companies that join Indonesian Stock Exchange (IDX), had to provides a present
fairly financial reporting. Measuring the reliability of financial reporting of
company is through using the independent auditor services. An auditor can analyze
company situation whether it is qualified, and also analyze company conditions for
the specific period time.
Auditor opinion become a measurement for several parties that involve in
financing the company. It can be used as a consideration for stockholders and
another parties as a decision-makers. (Currie Oni, et al, 2010) Thus, auditor now
must be cautious in putting forward an audit opinion taking account of any factors
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brought to your attention in producing a going concern audit opinion. (Petronela on
Achwaludin, 2011) Going concern can be seen from internal entity, total
investment, and entity ability to pay debt. So, if entity categorized as bankcrupt by
that decision model, prediction helps certainty on auditor opinion that related with
going concern entity.
Generally, going concern means that the audited entity will continue to exist
in the forseeable future – usually for a period of one year after the end of the fiscal
period, i.e. no intention or obligation for liquidation of the business entity or
significant reduction in its amount of operations is assumed for preparation and
presentation of financial statements (Rouhi, Ali et al, 2012).
The going concern audit report not only emphasizes the company‟s financial
difficulties, but also indicates that these difficulties are so serious as to raise
substantial doubt about the company‟s future existence (Kaplan, et al, 2012).
PSA No. 30 gives guideline for auditors in audit financial statement based on the
auditing standard set out by the Indonesian Accountant Association (IAI), in case
the auditor should evaluate whether there has been doubtfulness on the entity
capability to maintain its going concern (viability), they should identify the
information on the condition or certain events that indicate the presence of big
doubt against the entity capability to maintain its going concern, such as negative
trend, other clue on possible financial difficulty, internal problem and external
problem already occurred. With entity‟s doubt to be able to conduct its business
continuity, then the auditor can give going-concern opinion (modification opinion).
This opinion is a bad news for intersted users of financial statemnet. Most obstacle
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appeared very difficult to predict continuity an entity, auditors held dilemma among
morals and ethics on giving going-concern opinion. There is a cause hypothesis
self-fulfilling prophecy that declare if auditor give going-concern opinion, entty will
bankcrupt earlier because investor cancelled the investment or creditor that taking
back the funds (Venuti, Elizabeth K, 2007).
Auditor have to detect the material misstatements and the company‟s ability
to continue their business/going concern. Auditor has to able see the going concern
company, not only audit the financial statements. This Statement on Auditing
Standards (SAS) addresses the auditor‟s responsibilities in an audit of financial
statements with respect to evaluating whether there is substantial doubt about the
entity‟s ability to continue as a going concern.
Continuation of an entity as a going concern is assumed in financial
reporting in the absence of significant information to the contrary (Nevius Alistair.
M, 2012).(Foroghi, Darosh 2012) Consequently, we use going-concern reporting
accuracy as a proxy of audit quality because it is not reflected by client size and can
measure auditors‟ independence precisely. Ordinarily, information that significantly
contradicts the going concern assumption relates to the entity's inability to continue
to meet its obligations as they become due without substantial disposition of assets
outside the ordinary course of business, restructuring of debt, externally forced
revisions of its operations, or similar actions (Nevius, Alistair 2012).
Thus, the going-concern assessment is a matter of auditors‟ professional
judgement, and under SAS No.570, auditors are required to report based on their
knowledge of the client at the time of reporting (Foroghi, Darosh2012).
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Company size is one of variable that determine scale of company bussiness.
Through company size, public will see intencity of company activities, profit,
assets, liability, and also financial risks. Another aspect such as management
performances, can predict by seen company size. Big company needs to be control
continuously to prevent lack of management performances and achieve present
fairly financial statements. Through good performances, they may get higher
achievement and improve ability as a professional management team. The effects,
quality of financial statements is reliable and relevance. If it is not, then auditor will
found the doubt and give unqualified-modified opinion. Company size influences
the going concern of company. Many factors such as total assets, ability to fulfill
the debt according to the contract, relevance data of finance and internal control,
that being concern for auditor to audit the company. If it is inappropriate with
company real condition, or there is financial distress held, so auditor might be attest
going concern audit opinion. Through audit quality, company represent their
performances on handling financial and operating activities. The importance of
company size, audit quality, audit tenure, and audit pricing to going concern audit
opinion, auditor can predict company performances and their condition, analyze the
failure and explain it well with standards, according to their experiences and
knowledge as an auditor.
Company size become a benchmark for measure the scope of company on
running their business. The bigger company size, the bigger business they owned.
How much their capital, its influence to revenue and expense that they got. Also the
risk on business that they have to avoids, such as financial distress that mostly held
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causing by negative working capital, negative retained earnings, and bottom line
loss. The office size is measured in two different ways: one based on the number of
audit clients in each office and the other based on a total of audit fees earned by
each office. Our results show that the office size has significantly positive relations
with both audit quality and audit fees, even after controlling for national-level audit
firm size and office-level industry expertise. These positive relations support the
view that large local offices provide higher-quality audits compared with small
local offices, and that such quality differences are priced in the market for audit
services (Choi, Jong-Hag et al,2010).
Audit Quality is the most important factor to implies effectiveness,
efficiency an audit report. Through audit quality, another parties can classified
hows the opinion from independent auditor runs well to the company. If the audit
opinion given by auditor is qualified, so the going concern company will continue
for the specified period time. So we can conclude the audit report is qualified. But
if its not, so the quality of audit report cannot be responsible. The audit report that
made by auditor have to be responsible. (Choi, Jong-Haget al, 2010) The anecdotal
evidence on the collapse of Enron, which was audited by the Houston office of
Arthur Andersen, is a good example that demonstrates the importance of office-
level audit quality.
Improved quality is a function of not only the auditor's detection of material
misstatements, but also the auditor's behavior towards this detection (Al-Thuneibat,
et.al,2011). Therefore, if the auditor rectifies the discovered material misstatements,
a higher audit quality results, while failure to correct material misstatements upon
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detection and prior to issuing a clean audit report (or moreover failure to uncover
material misstatements) obstructs the improvement of audit quality (Johnson in Al-
Thuneibat, et.al, 2011). Therefore, improving the audit quality would provide
reasonable assurance about the accuracy of reported accruals and as a result, attest
for earnings of higher quality (Al-Thuneibat, et.al, 2011). Long auditor-client
relationships have the potential to create closeness between the auditor and the
client, enough to deter the auditor's independence and reduce the audit quality (Al-
Thuneibat, et.al, 2011).
Therefore, if the auditor rectifies the discovered material misstatements, a
higher audit quality results, while failure to correct material misstatements upon
detection and prior to issuing a clean audit report (or moreover failure to uncover
material misstatements) obstructs the improvement of audit quality (Johnson et al.,
on Al-Thuneibat, et.al, 2011).
Audit Tenure is a length time auditor working on contract
(Bamber&Iyer,2005). Audit tenure affects objectivity through prolonged
association with the client, since the auditor needs to be independent in order to be
objective. However,audit firm tenure is important for building familiarity with the
client‟s business and assisting the client to establish effective controls (Bonner on
Boateng 2011). Statictical analysis of data shows that, audit firm tenure affects the
audit quality adversely (negatively). Audit quality deteriorates, when audit firm
tenure is extended as a result of the growth in the magnitude of discretionary
accruals. Meanwhile, data analysis did not reveal that the audit firm size has any
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significant impact on the correlation between audit firm tenure and audit quality
(Al-Thuneibat, et.al, 2011).
Audit tenure influences significantly to going concern audit opinion that
given by auditor, the longer auditor relation with auditee, so it might decrease
probability of auditee gets going concern audit opinion. But auditor from big four
mostly do objective audit, so they conclude company as a going concern if it is
need, because auditor keep their reputation and good will.
Audit pricing which are equal to audit costs in a competitive equilibrium,
are a function of (1) client characteristics such as client size, client complexity, and
client-specific risk, and (2) auditor characteristics such as audit firm size and
industry expertise at the national level (Choi et.al,2008).
In Enron case, (Boynton C. Williams, 2006) on December 2, 2001, Enron
filed for bankruptcy protection. Although there might have been doubt about
Enron‟s ability to continue as a going concern, the company had access to
significant debt and equity markets when auditor issued an opinion on the financial
statements. Given the economic conditions at the time of the auditor‟s report,
Andersen LLP concluded that there was not substantial doubt about Enron‟s ability
to continue as a going concern. A significant portion of Enron‟s subsequent
collapse was its inability to generate operating cash flow in 2001, something that
was not known at the auditor‟s report date. Althogh Andersen was heavily critized
for its failure to find material misstatement in Enron‟s report on financial position
and results of operations (debt to equity should have been 5.3:1, and net income
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should have been $847 million rather than $979 million), there have been few
criticisms of the fact that it did not issue the going-concern opinion.
Auditors responsibility is to detecting debt default, company‟s continuation
of financing whether is it can be concluded as a going concern company for a
period time. The auditor‟s evaluation is based on the auditor‟s knowledge of
relevant conditions and events that exist at, or have occured prior to, the date of
auditors report. Information about such conditions or events is obtained from the
application of audit procedures to achieve audit objectives that are related to
management assertions embodied in financial statements. (Louwers J. Timothy,
et.al, 2007) Auditors are responsible for determining any substantial doubt about a
company‟s ability to continue as a going concern.
AU 341, The Auditor’s Consideration of an Entity’s Ability to Continue as a
Going-Concern, establishes a responsibility for the auditor to evaluate whether
there is substantial doubt about the client „s ability to continue as a going-concern
for a reasonable period of time, not to exceed one year beyond the date of financial
statements being audited (generally one year from the balance sheet date).
Ordinarily, information that would raise substantial doubt about the going concern
assumptions relates to the entity‟s inability to continue to meet its obligations as
they become due without the substantial disposition of assets outside the ordinary
course of business, restructuring of debt, externally forced revisions of its
operations, or similiar actions.
When the auditor concludes that there is substantial doubt aboutthe entity‟s
ability to continue as a going concern during the year following the date of the
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financial statements, she or he should state this conclusion in the audit report. If
management includes adequate disclosures in financial statements concerning the
entity‟s ability to continue as a going concern, the auditor will issue an unqualified
opinion on the financial statements with an additional paragraph explaining the
going concern uncertainty.
Based on the above cases, auditors responsibility is not only check the
material misstatement and management performances only, as an independent
parties they have to do objectives prediction about entity‟s ability for specific peiod
time i.e one year later. Some auditor may not confess the true entity‟s condition. It
is because of manager that manipulate financial repoting. They hide entity‟s
problem because they won‟t get going concern audit opinion. The impact may
appear one year later that entity‟s failed to fulfill their debt, that called debt default.
Operating cost that increase continously, and entity can not solve the problem. It
may cause entity‟s failed to continue business, and conclude as a bankcrupt
(Boynton C. Williams, et.al, 2006).
A study by (Al-Thuneibat, et.al, 2011) data analysis did not reveal that the
audit firm size has any significant impact on the correlation between audit firm
tenure and audit quality. Statistical analysis of data shows that, audit firm tenure
affects the audit quality adversely (negatively).
A study by (Shahshahani, Amir et al. 2012), in contrast, our results show
that financial reporting risk, management integrity risk, and internal control risk are
positively associated with the level of planned audit effort in 2002, and over the
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following year these risk responses increase. Management integrity risk is
positively associated with planned realization rates in 2002.
This research is the replication of study conducted by (Shahshahani, Amiret
al. 2012). His research states that only eleven of the 54 companies had received
going-concern modified opinion in their audit report and the Audit Organization of
Iran audit 42 % (23 out of 54) of the sample. The results indicate that over this
extended period, Audit Organization of Iran (as a big firm) do not have higher
going-concern reporting accuracy than other smaller audit firms of Iranian
Association of Certified Public Accountant). The difference to the previous study as
can be seen on independent variables. The writer focusing on the influances of four
independent variables such as company size, audit quality, audit tenure, audit
pricing to the going concern audit opinion in Indonesian Stock Exchange. Based on
the research background, the researcher is interested in conducting research
entitled:
“The Influences of Company Size, Audit Quality, Audit Tenure, and Audit
Pricing to the Going Concern Audit Opinion (GCAO)”
(Empirical Studies to the Property Company Listed in Indonesian Stock Exchange
Year 2013-2015)
This research is replication from the previous research that done by Abdul
Muchsin, 2010. The difference this research with the previous are:
1. Researcher use the different independent variable such as, company size,
audit quality, audit tenure, and audit pricing. While the previous research
use audit delay, opinion shopping, debt default, proxy going concern.
12
Purpose of using the different variables to know other possibilities that
might be more influences auditor in order to attests going concern audit
opinion. Beside advice from previous research, those variable also part of
personal characteristic that influence to continuity an entity.
2. Hypothesis test method in this research use multiple regression analysis to
know the influence varible relation that use dummy category.
3. Sample that used in this research is Property Company listed in Indonesian
Stock Exchange period 2013-2015, while the previous research only use
two years data.
B. Problem Formulation
Based on the background of the study, the problem is formulated as:
1. Does the company size influence to the going concern audit opinion?
2. Does the audit quality influence to the going concern audit opinion?
3. Does the audit tenure influence to the going concern audit opinion?
4. Does the audit pricing influence to the auditors performances on
assessing company?
5. Do the company size, audit quality, audit tenure, and audit pricing
influences continously to the going concern audit opinion?
C. Research Objectives and Benefits
1. Research Objectives
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a. To analyze whether company size has impact to the going concern
audit opinion.
b. To analyze whether audit quality has impact to the going concern
audit opinion.
c. To analyze whether audit tenure has impact to the going concern
audit opinion.
d. To analyze whether audit pricing has impact to the going concern
audit opinion.
e. To analyze whether company size, audit quality, audit tenure, and
audit pricing has continously impact to the going concern audit
opinion.
2. Research Benefits
a. Practitioners
1) Company
a) Showing the effectively of manager performances on doing his
mandatory on financial reporting.
b) Minimize fraudulent issues, lack of management performance,
manipulating report, and integrity risks.
c) Improve transparency and internal control system in company.
2) Investors
This research can be use as material for investor that wants to know
about financial condition and benefit from invest share and obligation from
14
an entity, absolutely it is important to see the possibilities the continuity
and bankcrupt from entity that sell the securities.
3) Creditor
Information about bankcrupt is beneficial to do decision making for
who is worthy to get loan, and beneficial for monitoring the loan itself.
4) Government
Several business sector, government institution are responsible to
montoring continuity of business (for example, banking sector).
Government also have business entity (BUMN) that also have to monitored.
Government institution have the interest to detect bankcrupt alert suppose
to do an action that can be done earlier.
5) Auditor
This research can be use as auditor consideration to do audit process,
in order to face client with similiar condition as the case on this research.
b. Academics
Academically, researcher hope the result can contribute to theory
development in Indonesia, especially about going concern. This research hope
can be use as reference, discussion material to readers about problem that related
with going concern. Results from this reseach will add the knowledge to
academics about company size, audit quality, audit tenure, and audit pricing to
going concern audit opinion, also as reference to the next research.
c. Researcher
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Give the opportunity to researcher to learn about going concern audit
opinion more wide scope.
d. Other researchers
This research intended to create opportunity for other researchers to used
as additional reference for any further research regarding similiar theme.
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Chapter II
Literature Review
A. Grand Theory
This literature review refers to the theoretical basis of agency theory, Going
Concern Audit Opinion, company size, audit quality, audit tenure, audit pricing.
1. Agency Theory
An agency is defined as a consensual relationship between two parties,
whereby one party (agent) agrees to act on behalf of the other party (principal). An
agency relationship exists between shareholders and managers because the owners
don‟t have the training or expertise to manage the firm themselves, have other
occupations, and are scattered around the country and the world (Schroeder et al,
2011).
Breda (1992) states that agency relations are a contractual relationship
between principals and agents, principals delegating specific tasks in accordance
with agreed contracts or decision making to agents. Agent will take the best action
in the interest of principals. Principals will reward the agent's work. The powers
and responsibilities of agents and principals are stipulated in the contract of work
on mutual consent (Ujiyanto, 2010).
The agency problem will arise when there is a conflict of interest between
principals and agents. Each side seeks to maximize personal interests. Principals
want the end result of a decision that generates profits as much as possible or
increases the value of investment in the company. Agent also must have a personal
interest to be achieved that is acceptance of adequate compensation for the
17
performance performed. Principals assesses agent performance based on its ability
to increase profits. The higher the amount of profit that will be generated by the
management (agent), principals will get higher dividends, then the agent is
considered successful or perform well so it deserves a high incentive. Agent also
met the demands of principals in order to get high compensation (Elqorni, 2009).
Agent is morally responsible for optimizing principals' profits. But on the
other hand, agents also have an interest in maximizing their personal well-being. So
most likely agents do not always act in the interests of principals (Jensen and
Meckling, 1976).
Manager of the company is more aware of internal conditions and prospects
of the company in the future than the owners (shareholders). Information would
trigger a condition called information asymmetry. The asymmetry between the
management (agent) with the owner (principal) can provide an opportunity for
managers to manage earnings in order to mislead the owners (shareholders)
regarding the economic performance of companies (Ujiyanto and Pramuka, 2007).
The financial statements are presented by the agent (management) to signal
the user about the condition of the company. If the financial statements do not
reflect the actual company conditions, it will affect the decision-making by the user.
Therefore, to minimize the existence of information asymmetry required an
independent third party as mediator relationship between principals and agents.
This third party serves to monitor the behavior of agents whether acting in
accordance with the wishes of principals (Dewayanto, 2011: 84).
18
According to Jensen and Meckling (1976), agency relationship as a contract
under which one or more person (the principal (s)) engage another person (the
agent) to perform some service on their behalf which involves delegating some
decision making authority to the agent. If both parties to the relationship are utility
maximizers, there is good reason to believe that the agent will not always act in the
best interest of principal. The principal can limit divergences from his interest by
establishing appropriate incentives for the agent and by incurring monitoring costs
designed to limit the aberrant activities of the agent. In addition, in some situations,
it will pay the agent to expend resources (bonding costs) to guarantee that he will
not take certain actions which will harm the principal or to ensure that the principal
will be compensated if he does take such actions.
However, it is generally impossible for the principal or the agent at zero cost
to ensure that the agent will make optimal decisions from the principal‟s viewpoint.
In most agency relationships, the principal and the agent will incure positive
monitoring and bonding costs (non-pecuniary as well as pecuniary), and in
addition, there will be some divergence between the agent‟s decisions and those
decisions which would maximize the welfare of the principal. The dollar equivalent
of the reduction in welfare experienced by the principal as a result of this
divergence is also a cost of the agency relationship, and we refer to this latter cost
as the “residual loss” (Jensen and Meckling, 1976).
19
2. Going Concern
IAI (2011:341.2): Defines going concern as doubt of the ability of the
business unit to maintain its survival for a reasonable period of time, no later than
one year from the date of audited financial statements.
According to Belkoui (2007:271) going concern is a proposition stating that an
entity will be expected to operate indefinitely or not directed towards liquidation. A
continuous and sustained operation is necessary to create a consequence that
financial statements published in a period are temporary because they are still a
continuous series of reports.
PSA no.30 (SPAP, 2011:341.1) States that going concern is used as an
assumption in the financial statements as long as there is no evidence of
information that shows the opposite. Usually information that is significantly
considered contrary to the assumption of business continuity of a business entity is
related to the inability of a business entity to meet its obligations at maturity
without selling the asset to an outsider through ordinary business, debt
restructuring, And other similar activities.
3. Auditor’s Responsibility for Going Concern
In section Section 341 paragraph 3 it is stated that the auditor is responsible
for evaluating whether there is a great doubt about the entity's ability to maintain its
viability within a period of time, not later than one year from the date of the audited
financial statements in the following manner (IAI, 2012):
1. The auditor considers whether all the results of the procedure carried out
indicate a great doubt about the entity's ability to maintain its viability within a
20
reasonable period of time (not later than one year from the date of financial
reporting being audited). Additional information on conditions and events may
be necessary and evidence supporting information that reduces the auditor's
doubts.
2. If the auditor believes that there is a great doubt about the entity's ability to
maintain its survival within a reasonable period of time, the auditor shall:
a. Obtain information about management plans aimed at reducing the
impact of these conditions and events.
b. Determine whether the possibility that the plan can be effectively
implemented.
c. After the auditor evaluates the management plan, he concludes whether he
still has great doubts about the ability of the entity to maintain its viability
within a reasonable period of time.
SA section 341 paragraph 4 states that the auditor is not responsible for
predicting the conditions and events that will come. The fact that the entity is likely
to end its survival after receiving a report from an auditor who does not show great
doubts, within a year of the financial statement date does not necessarily indicate
inadequate audit performance. Therefore, the exclusion of major doubts in the audit
report should not be seen as a guarantee of the entity's ability to maintain its
survival (Widyantari, 2011: 24).
4. Audit Going Concern Opinion
A going concern is an audit opinion issued by the auditor to evaluate whether
there is doubt about the ability of the entity to maintain its survival (SPAP, 2011).
21
Auditors determine acceptance of going concern audit opinion if in the audit
process found conditions and events that lead to doubts on the survival of the
company. The following are examples of conditions and events that lead to doubts
about the viability of the company (SA Section 341):
1. Trend negative. Examples: repeated operating losses, lack of working capital,
negative cash flows from business activities, important bad financial ratios.
2. Other clues about possible financial difficulties. Examples: failure to fulfill
obligations or similar agreements, delinquency of dividend payouts, supplier's
refusal to apply for ordinary credit purchase, debt restructuring, the need to
find new sources or funding methods, or the sale of most assets.
3. Internal problems. Examples: work strikes or other labor difficulties, heavy
reliance on successful projects, long-term non-economic commitments, the need
to significantly improve operations.
4. External problems that have occurred. Example: a court filing, a lawsuit, or
other problems that may jeopardize the entity's ability to operate; Loss of
important franchisees, licenses or patents; Loss of major customers or suppliers;
Losses due to major disasters such as earthquakes, floods, droughts, uninsured
or insured but with inadequate coverage.
Standard Professional Public Accountant (SPAP, 2011) section 341 states if
the auditor does not doubt the ability of the business unit to maintain the going
concern within a reasonable time period, then the auditor gives unqualified opinion.
If the auditor doubts the ability of a business to maintain its viability within a
reasonable time period, then the auditor shall evaluate the management plan. The
22
auditor will provide an unqualified opinion with explanatory language if the
company's management plan can be effectively implemented to overcome the
impact of conditions and events that cause auditor's doubts about the viability of its
business.
If the auditor considers that the management plan could not effectively
mitigate the negative impact of the condition or event, the auditor declares no
opinion. Fair opinion with an exception is given to the auditee if the auditor doubts
the survival of the company and the auditor concludes that management does not
disclose and about the nature, impact, conditions and events that cause the auditor
to doubt the survival of the company. If disclosure in the management plan is
inadequate and no disclosure is made, whereas the impact is highly material and
there is a deviation from the general acceptable accounting principles, the auditor
will give an unfair opinion (Sari, 2012: 20).
5. Company Size
Dewayanto (2011: 88) states that auditors are more often issued a
modification of going concern audit opinion on smaller companies. This is possible
because the auditor believes that a larger company can solve the financial
difficulties it faces than smaller companies. In addition, larger firms spend more
audit fees higher than those offered by smaller companies. In relation to the loss of
significant audit fees, the auditor may doubt the opinion of going concerns at large
companies (McKnown et al., 1991).
The size of the client company that is proxied with the total natural log of
the company's assets shows the company's ability to keep the business going. The
23
higher total assets owned, the company is considered to have a large size so as to
maintain the continuity of its business. Large companies have better capabilities in
managing the company and produce higher quality financial reports (Junaidi and
Hartono, 2010: 9). The smaller the scale of the firms shows the smaller firms'
ability to manage their business. This causes the company more likely to get going
concern audit opinion (Widyantari, 2011: 55).
6. Audit Quality
a. Definition of Audit Quality
According to DeAngelo (1981) audit quality is the assessment by the market
of the combined probability that an auditor will simultaneously discover an
anomaly or significant irregularity in the client company‟s accounting system and
publish this anomaly or irregularity. When audit quality is costly to evaluate, self-
interested individuals have incentives to devise alternative arrangements which
enable quality differentiated audits to be exchanged.
According to (Yuniarti, 2011), audit quality is the bends to the which a set
of inherent characteristics fullfill requirements of an audit. According to Riyatno in
(Yuniarti, 2011), audit quality as something that is abstract, difficult to measure and
can only be perceived by the users of audit services, so that until now there is no
uniform definition of audit quality. Audit quality embraces the concepts of
professional competence and the meeting or exceeding of professional standards
(both technical and ethical) in expressing an opinion on audited financial
statements, performing other attest services, being associated with unaudit financial
statements, and providing other types of accounting services.
24
Audit quality proceeds primarily from a firm‟s enlightened self-interest and form
the concept of integrity.
According to PCAOB audit quality as meeting investor needs for independent and
reliable audits and robust audit committee communication on:
1) Financial statements including related disclosures
2) Assurances about internal control; and
3) Going concern warnings
Based on the definition above, audit quality is a value of audit performances
done by auditor that can be accounted for the validity.
b. Characteristics of Audit Quality:
According to (Yuniarti 2011) there are eight characteristics of audit quality.
1) Significance – How important is the matter that was examined in the audit?
This, in turn, can be assessed in several dimensions, such as the financial
size of the auditee and the effects of the performance of the auditee have on
the public at large or on major national policy issues.
2) Reliability – Are the audit findings and conclusions an accurate reflection of
actual conditions with respect to the matter being examined? Are all
assertions in the audit report or other product fully supported by the data
gathered in the audit?
3) Objectivity – Was the audit carried out in an impartial and fair manner
without favor or prejudice? The auditor should base his assessment and
opinion purely on fact and on sound analysis.
25
4) Scope – Did the audit task plan properly address all elements needed for a
successfull audit? Did execution of the audit satisfactorily complete all the
needed elements of the task plan?
5) Timeliness – Were the results delivered at an appropriate time? This may
involve meeting a statutory deadline or delivering audit results when they
are needed for a policy decision or when they will be most useful in
correcting management weaknesses.
6) Clarity – Was the audit report clear and concise in presenting the results of
the audit? This typically involves being sure that the scope, findings and
any recommendations can be readily understood by busy executives and
parliamentarians who may not be experts in the matters that are addressed
but may need to act in response to the report.
7) Efficiency– Were the resources assigned to the audit reasonable in the
light of the significance and complexity of the audit?
8) Effectiveness – Did the findings, conclusions and recommendations get an
appropriate response from the auditee, the government and/or parliament.
7. Audit Tenure
a. Definition of Audit Tenure
Long tenure is assumed to lead to less objectivity in the auditor's behavior,
where a "learned confidence" in the client is developed (Al-Thuneibat, 2011).
Gheiger and Raghunandan (2002) state tenure is the length of client auditor
relationship measured by the number of years. When the auditor has a long time
relationship with his client, this will encourage a better understanding of the client's
26
financial condition and therefore they will be able to detect going concern
problems. In a second point of view, keeping in touch with the same public
accounting firm for long periods is considered more economical for the client. The
existence of the relationship between the auditors with his client in a long time is
feared will make the auditor lose its independence. Because between the auditor
and the client is tied to a comfortable and mutually beneficial relationship so that
the quality of the audit becomes low. Loss of auditor independence can be seen
from the auditor's difficulties in giving a going concern audit opinion to his client
(Sari, 2012: 21). Based on the definition above, audit tenure is a length relationship
between auditor and client based on their contract for audit the financial statement.
b. Characteristics of Audit Tenure
Johnson et al. (2002) They classify audit firm tenure into three categories:
I. short (two to three years),
II. medium (four to eight years), and
III. long (nine or more years).
They use the group of medium tenure as a benchmark and find that short
tenure is associated with larger absolute discretionary accruals but long tenure is
not, which suggest that long audit firm tenures are not associated with a decline in
earnings quality.
27
8. Audit Pricing
a. Definition of Audit Pricing
According to Choi et al. (2008) predict that audit fees/audit pricing, which
are equal to audit costs in a competitive equilibrium, are a function of (1) client
characteristics such as client size, client complexity, and client-specific risk, and
(2) auditor characteristics such as audit firm size and industry expertise at the
national level.
b. Characteristics of Audit Pricing
Consistent with this view, the extant audit pricing models, developed first
by Simunic (1980) and further extended by Choi et al. (2008), predict that audit
fees, which are equal to audit costs in a competitive equilibrium, are a function of
(1) Client characteristics such as client size, client complexity, andclient-specific
risk, and
(2) Auditor characteristics such as audit firm size and industry expertise at the
national level. (Choi, et al 2010).
28
B. Previous Research
This research is a development from previous studies that the results of this
study are expected to contribute over previous studies. The results of previous
research can be seen in the table below:
No. Researcher Variable Methodology Result
1. Ali
Abedalqader
Al-Thuneibat,
2010
1. Audit
Tenure (X1)
2. Firm Size
(X2)
3. Audit
Quality (Y)
Quadratic Form
Approach
The length of the audit
firm-client relationship
(audit-firm client
engagement was found
to negatively affect the
quality of audit reported
by publicly traded firms
in Jordan.
2. Jong-Hag
Choi, 2010
1. Audit
Office Size
(X1)
2. Audit
Quality (X2)
3. Audit
Pricing
Undesign
Abnormal
Accrual
The office size has
significantly positive
relations wih both audit
quality and audit fees,
even after controlling
for national-level audit
firm size and office-
level industry expertise.
3. Dr. Daruosh
Foroghi, PhD,
2012
1. Audit Firm
Size (X1)
2. Going-
concern
reporting
accuracy (Y)
Logistic
Regression
The findings indicate no
association between the
size of audit firm ad
going-concern reporting
accuracy.
4. Jean C. Berard,
2010
1.Engagement
Audit Partner
Tenure (Y)
2. Audit
Planning (X1)
3. Audit
Pricing (X2)
Logistic
Regression
Higher planned realization
rates on audits having the
same engagement partner
for more than five years, a
longer tenure than is now
allowed for public
companies following the
Sarbanes-Oxley Act.
29
C. Logical Framework and Hypothesis
The relationship or interrelationship between independent variables and
dependent variable in this research can be described as follows:
1. Company Size to Going Concern Audit Opinion
Mutchler (1985) in Kartika (2012: 29) states that auditors are more often
issued a modification of going concern audit opinion on smaller companies.
The size of the company that is proxied with the natural longaritm of total assets
owned shows the company's ability to maintain business continuity. The higher
total assets owned, the company is considered to have a large size so as to
maintain the continuity of its business. Large companies have better ability to
manage the company and produce better quality financial reports (Junaidi and
Hartono, 2010: 9). The smaller the company's scale shows the company's
smaller capability in managing its business. This causes the company more
likely to get going concern audit opinion.
(Kevin et al, 2005) suggests that big companies have better capabilities in
maintaining their survival even when the company is experiencing financial
distress. By Karen, the auditor will delay giving going concern opinion in the hope
that the company will be able to overcome the bad condition in the coming year
(Widyantari, 2012: 55).
Several studies conducted by Mutchler et al. (1987), Rahayu (2009), Junaidi
and Hartono (2010), Warnida (2011), Widyantari (2011), Muttaqin and Sudarno
(2012), explained the negative relationship between company size and going
concern opinion. Rahayu's (2009), Warnida (2011), Widyantari (2011), Muttaqin
30
and Sudarno (2012) results show that firm size has a significant effect on
acceptance of going concern opinion.
The firm size relationship with the opinion of going concern is the bigger the
client company then the auditor will avoid giving go concern opinion, because big
company is considered better able to overcome the bad condition compared with
the small company. Research Junaidi and Jogiyanto (2010) showed that firm size
measured by natural longaritma of total assets did not significantly affect the
acceptance of going concern audit opinion. Based on the results of research Indira
Januarti, it can be concluded that,
H1: Company Size has a significant effect on the acceptance of going concern
audit opinion.
2. Audit Quality to Going Concern Audit Opinion
Measurement of previous research conducted by A.A. Ayu Putri Widyantari
(2011) shows that audit quality has no effect on going concern audit opinion. This
means that the public accounting firm affiliated with the public big four accounting
firm or not affiliated with the big accounting public accounting firm both provides
good audit quality and is independent in issuing a going concern audit opinion. The
results of this study are in line with the findings of Setyarno, Indira Januarti and
Faisal (2006). With the results of the study can be formulated hypothesis as
follows:
H2: Audit quality does not significantly influence the possibility of going
concern audit.
31
3. Audit Tenure to Going Concern Audit Opinion
Tenure audits are the period of engagement that occurs between the public
accounting firm and the same auditee. The longer the auditor relationship with the
client, it is feared the lower the disclosure of the inability of the company in
maintaining the continuity of its business. This will affect the acceptance of going
concern audit opinion toward the company (Junaidi and Hartono, 2010).
When the relationship between the auditor and the client of a public
accounting firm has been going on for years, the client can be viewed as a regular
source of income, potentially reducing the independence of the public accounting
firm (Widyantari, 2011: 58). There is a threat to the auditor's objectivity from its
familiarity with clients, leading to criticisms that it is not possible to expect the
auditor to conduct objective and unbiased assessments (Bazerman et al 2002). The
audit engagement relationship between the auditor and the old client will make the
auditor lose its independence, so to provide a going concern audit opinion is
difficult (Dewayanto, 2011: 89).
The research of Junaidi and Hartono (2010), Dewayanto (2011), and
Widyantari (2012) found a negative relationship between audit tenure and going
concern opinion. The results by Knechel and Vonstraelen (2007), Junaidi and
Hartono (2010), Muttaqin and Sudarno (2012), and Widodo (2011) found evidence
that audit tenure has a significant effect on going concern audit opinion.
Tenure audit relationship with going concern audit opinion is the longer the
audit engagement between auditor and client causes the auditor independence
32
decreases so that auditor is reluctant or more difficult to give going concern audit
opinion to his client.
H3: Tenure Audit has a significant effect on going concern audit
opinion.
4. Audit Pricing to Going Concern Audit Opinion
Like the suppliers of other professional services such as medical doctors and
lawyers, auditors take into account both the cost of delivering audit services and the
quality of audit services when pricing their services. Consistent with this view, the
extant audit pricing models, developed first by Simunic (1980) and further extended
by Choi et al. (2008), predict that audit fees, which are equal to audit costs in a
competitive equilibrium, are function of client characteristics such as client size,
client complexity, and client-specific risk, and auditor characteristics such as audit
firm size and industry expertise at the national level. In addition, recent studies by
Ferguson et al. (2003) and Francis et al. (2005) document that auditors with city-
based industry relationship are able to charge higher audit fees to their clients. So,
the following hypothesis:
H4: Audit Fees paid to auditors are not associated with the size of a
local engagement office, other things being equal.
33
Figure 2.1 Logical Framework
The Influences of Company Size, Audit Quality, Audit Tenure, and Audit
Pricing to the Going Concern Audit Opinion (GCAO)
Enron filed for bankruptcy protection
All X variables influences the going concern audit opinion
Auditing, Consideration of fraud in a Financial
Statement Audit
Environmental Accounting
(Y)
Basic Concept
Measurement
Disclosure
Advantage
Environmental Accounting
(Y)
Conceptual
Measurement
Disclosure
Advantage
Company Size (X1)
Regressions Logistics
Going Concern Audit
Opinion (Y)
Basic Concept
Measurement
Disclosure
Advantage
Audit Quality (X2)
Audit Tenure (X3)
Audit Pricing (X4)
34
Chapter III
Research Methodology
A. Research Scope
In this study, researcher conducted observations of the research title is
the influence of company size, audit quality, audit tenure, audit pricing to the going
concern audit opinion. The researcher uses SPSS application for data processing
where SPSS application is one of statistic applications that commonly used by the
other researchers in processing their data.
Based on the title, there are four independent variables and one dependent
variable of research. The influence of audit quality, audit tenure, and audit pricing
to the going concern audit opinion as the dependent variable.
B. Sampling Methods
The population is a collection of measurement data or observations
made to the people, things, or places. While the sample is a portion of the
population or in mathematical terms can be called as a subset or subsets of the
population. The population used in this study are:
1. All property companies listed on the Indonesia Stock Exchange (BEI)
2. Using the audited financial statements and reports obtained from the property
company BEI.
3. The required data is available to complete and publish the financial statements
have been audited by an independent auditor of the year (2013-2015).
4. Using the financial period from 1 January to 31 December and use the rupiah as
the reporting currency.
35
5. The sample in this study were obtained by purposive sampling method, with the
following criteria:
1) Auditee already listed on the Stock Exchange.
2) Auditee not out of IDX during the study period.
3) Publish financial statements audited by independent auditors.
Sample in this research is the property companies that listed in Indonesian Stock
Exchange.
C. Data Collection Method
The data used in this research is secondary data, namely a list of property
companies listed in Indonesia Stock Exchange (IDX) in the period 2013-2015 and
annual financial statements for 2013-2015. Collecting data in this study were
obtained from the Capital Market Reference Center at the Indonesian Stock
Exchange (BEI). In addition, data and other information obtained from journals,
textbooks, internet, and the Indonesian capital market directory.
D. Data Analysis Method
1. Hypothesis Testing
Test hypothesis is used logistic regression. Logistic regression analysis to test
the effects of these two variables, of which two or more independent variables that
have a ratio measurement types, as well as a dependent variable of type nominal
measurement. The regression test used to prove the influence of company size,
quality audits, and audit pricing related to going concern entity property companies.
Criteria for acceptance or rejection of the hypothesis with logistic regression:
a. If the results of significance <0.05 then Ha accepted
36
b. If the results of significance >0.05 then Ha is rejected
The model used to test this hypothesis are:
Y= a+ b1X1+b2X2+b3X3+b4X4+e
Description:
Y = Going Concern
a = constant
b1- b4 = coefficient regression
X1 = variable company size
X2 = variable audit quality
X3 = variable audit tenure
X4 = variable audit pricing
e = error term
2. Assess the feasibility of Regression Model
Feasibility regression model was assessed using the Hosmer and Lemshow's
Goodness of Fit Test. This model test the null hypothesis that the empirical data in
accordance with the model (there is no difference between the models with the data
so that the model can be said to be fit). As a result if (Ghozali, 2009): this was no
significant difference between the models with observations that the value of
Goodness fit model is not good because the model can not predict the value of
observations. If the statistical value Hosmer and Lemeshow's Goodness of Fit Test
is equal to or less than 0.05, the null hypothesis is rejected.
If the statistical value Hosmer and Lemeshow's Goodness of fit test is
greater than 0.05, the null hypothesis can not be rejected and mean model is able to
37
predict the value of observation, or it can be said that the model can be accepted
because according to the data observations (Ghozali, 2009).
3. Assessing Model Overall (Overall Model Fit Test)
This test is used to assess the models that have been hypothesized to be fit
or not with data. Hypotheses to assess model fit:
H0: hypothesized model fit to the data
H1: Model hypothesized does not fit with the data
From this hypothesis, that the model fit to the data, H0 should be accepted. The
statistics are used by Likelihood. Likelihood L of the model is the probability that
the hypothesized model drawing on data input. To test the null and alternative
hypotheses, L transformed into -2LogL. SPSS output provides two grades -2LogL
ie one for models that only include the constants A and one model with a constant
and free extras.
Reduction in value between -2LogL beginning with the next -2LogL shows
that the hypothesized model fit to the data (Ghozali, 2009). Log likelihood on
logistic regression similar to the notion of "Sum of Square Error" on a regression
model, so the decline Log Likelihood models regression model showed that the
better.
4. Coefficient of Determination
The coefficient of determination (R2) essentially measures how much
Traffic model in explaining variations in the dependent variable. The coefficient of
determination is between zero and one. R2 value is small means that the ability of
the independent variables in explaining the variation of the dependent variable is
38
very limited. A value close to the mean of independent variables provides almost all
the information needed to predict the variation of the dependent variable (Ghozali,
2009).
5. Classification table
The table shows the classification of the predictive power of the regression
model to predict the likelihood of the dependent variable. Strength prediction of the
likelihood of the dependent variable is expressed as a percent. Table classification
calculates an estimate of the true (Correct) and one (Incorrect) (Ghozali, 2009).
6. Descriptive Statistics
Descriptive statistics were used to analyze the data by describing the sample
data that has been collected in the actual conditions without means to create
generally accepted conclusions and generalizations. Descriptive statistical analysis
is used to give a general overview of the demographics of the respondents in the
study and description of the study variables.
7. Method of Logistic Regression
Testing hypotheses 1, 2, 3, and 4 using a logistic regression analysis. Logistic
regression was used to predict the statistical probability of occurrence of an event to
match the data on the function logit logistic curve. This method is a general linear
model used for binomial regression. Such as regression analysis in general, this
method uses several predictor variables, both numeric and category. Interpretation
logistic regression using odds ratios or probabilities.
Logistic regression was part of the regression analysis is used when the
dependent variable (response) is a dichotomous variable. Dichotomous variables
39
usually only consists of two values, which represent the appearance or absence of
an event that is usually given the number 0 or 1. Unlike the usual linear regression,
logistic regression assume no relationship between independent and dependent
variables in a linear manner.
E. Optimization of Variable
In this section will describe the definition of each variable used
accompanied with the operation and measures. The operationalization of these
variables are as follows:
1. Company Size (X1)
Factors the company will be measured using several variables. One is to use
variable size companies, where the variable will measure about the level of firm
size. And the variables on the size of the company using the natural logarithm.
2. Audit Quality (X2)
Audit quality is the probability of an auditor where to find and report on the
misappropriation of client's accounting system. Quality auditor measured using size
auditor specialization. Where the use of a dummy variable, 1 if the big four, 0 if the
non-big four
3. Audit Tenure (X3)
Audit Tenure is a length time auditor working on contract (Bamber&Iyer,
2005). Audit tenure affects objectivity through prolonged association with the
client, since the auditor needs to be independent in order to be objective.
However,audit firm tenure is important for building familiarity with the client‟s
40
business and assisting the client to establish effective controls (Bonner on Boateng
2011).
Audit tenure influences significantly to going concern audit opinion that
given by auditor, the longer auditor relation with auditee, so it might decrease
probability of auditee gets going concern audit opinion. But auditor from big four
mostly do objective audit, so they conclude company as a going concern if it is
need, because auditor keep their reputation and good will. This variable count by
length time of audit report release to public (from 31 december until maximum
three months later).
4. Audit Pricing
Audit pricing which are equal to audit costs in a competitive equilibrium, are a
function of (1) client characteristics such as client size, client complexity, and
client-specific risk, and (2) auditor characteristics such as audit firm size and
industry expertise at the national level. This variable count using natural logarithm.
41
Variable Operationalization
This table contains variables that used on this research such as, company size, audit
quality, audit tenure, audit pricing, and audit going concern audit opinion.
Researcher explain each variables with journal resources, indicator, and
measurement scale. The following is an operationalization variable table below:
Table 3.1
Variable Operationalization
No Variable Indicator Measurement Scale
1. Company Size
(X1)
Dr. Daruosh
Foroghi, PhD,
2012
Measured by natural log of total
assets from balance sheet
Ratio
2. Audit Quality
(X2)
Jong-Hag Choi,
2010
Dummy variable.
1 for big four and 0 for not big
four.
Nominal
3. Audit Tenure
(X3)
Ali Abedalqader
Al-Thuneibat,
2010
Measured by the length of the
audit firm-client relationship
for company, calculated in
years.
Ratio
4. Audit Pricing
(X4)
Tom Van
Caneghem, 2010
Measured by natural log of
professional fees
Ratio
5. Going Concern
Audit Opinion
(Y)
Dr. Daruosh
Foroghi, PhD,
2012
Dummy variable.
1 for company accept going
concern and 0 for company not
accept going concern opinion.
Nominal
42
Chapter IV
Research and Findings
A. Descriptive Statistic Analysis
Descriptive statistics are used to provide an overview of the theoretical range,
actual range, mean (average) and standard deviation of each variable Company
Size, Audit Quality, Audit Tenure, Audit Pricing, as follows:
Table 4.1. Descriptive Variables
Company Size (X1), Audit Quality (X2), Audit Fees (X3), Audit Tenure (X4),
and Going Concern (Y)
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
Company Size(X1) 63 2698917559 36022148489646 4884372725620.64 7834966869052.086
Audit Quality 63 .00 1.00 .2857 .45538
Audit Fees 63 5117016 97559160214 11366435222.11 20982173140.182
Audit Tenure 63 43.00 243.00 99.0952 32.25089
Going Concern 63 .00 1.00 .8571 .35274
Valid N (listwise) 63
Source : Output SPSS 22
43
Based on Descriptive table above from 63 sample companies showed that
for Company Size variable minimum value is equal to 2,698,917,559, its maximum
value is equal to 36,022,148,489,646, the average value is equal to
4,884,372,725,620.64 with deviation standard equal to 7,834,966,869,052,086.
For the Quality Audit variable with the minimum category value is 0 (Non
Big Four), the maximum value of the category is 1 (Big Four), the average value of
the category is 0.29, with the standard deviation of 0.46. For the Fees Audit
variable the minimum value is 5,117,016, the maximum value is 97,559,160,214,
the average value is 11,366,435,222.11, with standard deviation of
20,982,173,140,182.
For the Audit Tenure variable the minimum value is 243, the maximum value is
243, the average value is 99,095, with the standard deviation of 32,251. And for
Going Concern variable the minimum category value is 0 (Non Going Concern),
the maximum is 1 (Going Concern), the average value is 0.86, with the standard
deviation of 0.353.
1) Test Before Independent Variables
Based on table Classification Block 0 above shows if without involving
independent variables (company size, audit quality, audit fees, and audit tenure),
the ability of accuracy predicts that the happening of the going concern company
is 85.7% (54/63 * 100%) . Furthermore, based on the table variables in the
Equation shows the value of B = 1.179 or exp (1.179) = e1,179 = 6.00 where e =
2.72 this is due to the number of companies that are non-going concern is 9 and
44
the company is going concern is 54. And based on the table is also known Wald
statistic value, Wald test is used to test whether each logistic regression
coefficient whether significant or not significant. The Wald test is equal to the
square of the logistic regression coefficient ratio β and the standard error S.E. (Β /
S.E. = (1.792 / 0.360) ^ 2 = 24.766) with a significant value of 0,000> 0.05. This
means that the logistic regression coefficient is significant. So this logistic
regression model is good for predicting about independent variables. Table
Classification and variables in the equation can be seen on the following page.
Table 4.2. Classification Table Classification Table
a,b
Observed
Predicted
Going Concern
Percentage
Correct
Non Going
Concern
Going
Concern
Step 0 Going
Concern
Non Going
Concern 0 9 .0
Going Concern 0 54 100.0
Overall Percentage 85.7
a. Constant is included in the model.
b. The cut value is .500
sources: Output SPSS 22
Table 4.3. Variable In The Equation
Variables in the Equation
B S.E. Wald Df Sig. Exp(B)
Step 0 Constant 1.792 .360 24.766 1 .000 6.000
45
Based on the table of variables not in the Equation indicates whether each
independent variable has contributed to the healing effect of a going concern
company in a logistic regression model. The table states that the Company Size,
Audit Quality, and Tenure Audits are significant. In the table shows the significant
value of Quality Audit is more dominant than the significant value of Audit Tenure
and Company Size. This means that the most dominant Quality Audit variable can
cause a going concern company in a model so that the model is used better than
Tenure Audit and Company Size. The table variable not in the equation can be seen
on the following page.
Table 4.4. Variabel Not In The Equation
Variables not in the Equation
Score Df Sig.
Step 0 Variables X1 6.844 1 .009
X2(1) 7.467 1 .006
X3 3.828 1 .050
X4 4.955 1 .026
Overall Statistics 19.059 4 .001
Sources : Output SPSS 22
2) Model Feasibility Test (Goodness of Fit)
The model feasibility test on logistic regression will be tested against the
accuracy between the logistic regression model prediction and the observed data
stated in the model of goodness of fit test. This test is necessary to ensure no
weakness or bias in predicting the model. A good logistic regression model shows
46
no difference between data from observation and data obtained from the prediction
result. Testing on the absence of differences between these predictions and
observations is done by Hosmer and Lemeshow's test using the Chi-Square method.
The hypothesis used to assess the feasibility of the model is as follows:
H0 : Models hypothesized fit with data
Ha : the hypothesized model is not fit with data
B. Test Hosmer and Lemeshow
The Hosmer and Lemeshow's Goodness of Fit Test is used to test the null
hypothesis (H0) that empirical data match or match the model (no difference
between the predicted data and the observed data). The basis used to make a
decision is to look at the value of Hosmer and Lemeshow Googness-of-fit test
statistics equal to or less than 0.05, then the null hypothesis (H0) is rejected which
means there is a significant difference between the model and the observation value
or Googness-of -fit model is not good because the model can not predict its
observation value. If the Hosmer and Lemeshow Googness-of-fit test statistics are
greater than 0.05 then the null hypothesis (H0) is accepted which means no
significant difference between the model and the observed value or the Googness-
of-fit model is good because the model can predict its observation value . Hosmer
and Lemeshow Chi-square model step 5 is also used to prove whether the model is
efficient or feasible.
Below is presented test results Hosmer and Lemeshow Goodness-of-fit test
statistic
47
Table 4.5. Hosmer and Lemeshow Test
Hosmer and Lemeshow Test
Step Chi-square df Sig.
1 2.108 8 .978
Source : Output SPSS 22
Based on the Hosmer and Lemeshow's Goodness of Fit Test model table shows that
the chi-square value is 2.108 with a significance value of 0.978. Since the value of
significance is greater than α = 0.05, then H0 is accepted. This means that the model
is able to predict the company's going concern or the model is able to predict the
value of observations or can be said that the model is acceptable because it matches
the observation data (Ghozali, 2006).
C. Overall Model Testing (Overall Model Fit)
1. Chi Square Test
According to Ghozali (2005) the chi-square test in addition to being used to test the
feasibility of the model can also be used to see the overall model of the data
performed by comparing the value between -2 log likelihood at the beginning
(block 0: initial) with the log-2 likelihood value at End (block 1: method) step 1 in
the Iteration History table. If the results of the comparison of both the decline, then
the model shows a good regression model. Decrease -2 log likelihood can be seen
in table 4.6 as follows:
Table 4.6. Itteration History Iteration History
a,b,c
48
Iteration -2 Log likelihood
Coefficients
Constant
Step 0 1 52.783 1.429
2 51.687 1.752
3 51.675 1.791
4 51.675 1.792
a. Constant is included in the model.
b. Initial -2 Log Likelihood: 51.675
Testing on block 0 step 4 or this test is done by entering all predictor
obtained value -2 log likelihood equal to 51,675. The Log-Likelihood value of the
constant (c) is 51.675 after involving several predictors: Company Size, Audit
Quality, Audit Fees, and Tenure Audit on the summary and omnibus model Tests
of Model coefficients obtained value -2 log Likelihood of 27,424. This shows a
considerable decrease in the value of going concern probability from 21 property
companies that is 51.675 - 24,251 = 27,424 This decrease indicates the relationship
between independent variable with dependent variable. The Likelihood Log-2
decrease results are presented in the chi-square values in the omnibus table test of
the model coefficient model step 1 as follows:
Table 4.7. Itteration History
Iteration Historya,b,c,d
Iteration -2 Log likelihood
Coefficients
Constant X1 X2(1) X3 X4
Step 1
1 40.146 5.988 .175 .786 -.184 -1.091
2 31.091 8.242 .439 1.390 -.395 -1.723
49
3 26.278 8.896 .825 2.173 -.710 -2.086
4 24.490 10.418 1.174 3.074 -1.033 -2.469
5 24.256 11.865 1.326 3.584 -1.196 -2.724
6 24.251 12.233 1.348 3.690 -1.225 -2.776
7 24.251 12.248 1.349 3.693 -1.226 -2.778
8 24.251 12.248 1.349 3.693 -1.226 -2.778
a. Method: Enter
b. Constant is included in the model.
c. Initial -2 Log Likelihood: 51.675
d. Estimation terminated at iteration number 8 because parameter estimates changed by less than
.001.
Source : Output SPSS 22
Table 4.8. Omnibus Test
Omnibus Tests of Model Coefficients
Chi-square Df Sig.
Step 1 Step 27.424 4 .000
Block 27.424 4 .000
Model 27.424 4 .000
Source : Output SPSS 22
The overall model coefficient test (overall model) of the 4 overall predictors was
performed using omnibus test of model coefficient. Omnibus test test results
obtained chi-square value (decrease value -2 log likelihood) of 27.424 with a
significant value of 0.000. Since the value is significantly smaller than the value of
α = 0.05, this means that there is a significant influence of the four predictors of
Company Size, Audit Quality, Audit Fees, and Audit Tenure on going concern
50
firms or together to four predictors can Explains the happening of going concern
companies on 20 property companies.
2. Cox and Snell’s R Square and Negelkerke’s R Square
Cox and Snell's R Square is a measure of how to translate the same as R2
(coefficient of determination) in multiple regression. But since the maximum value
of Cox and Snell's Square is usually smaller than one, it is difficult to interpret as
R2 and rarely used.
Table 4.9. Model Summary Model Summary
Step -2 Log likelihood
Cox & Snell R
Square
Nagelkerke R
Square
1 24.251a .353 .631
a. Estimation terminated at iteration number 8 because
parameter estimates changed by less than .001.
Source : Output SPSS 22
Nagelkerke's R Square value of 0.631 is a modification of Cox & Snell R
Square coefficients for maximum values to reach one and have a range of values
between 0 and 1, just as the coefficient terminated R2 on multiple linear regression.
The value of Nagelkerke's R Square coefficient is generally larger than Cox &
Snell's R Square coefficient but tends to be smaller than the coefficient of
determination R2 in multiple linear regression.
The value of Nagelkerke's R Square is 0.631 indicating that the variable
dependent variable can be explained by the independent variable variability of
63.1% and the remaining 36.9% is explained by other variables outside the model.
Furthermore, the value of Cox and Snell R-Square step 1 is 0.353 (35.3%) shows
51
that logistic regression model able to explain 35.3% variation of variable
dependent.
D. Classification Test 2 X 2
Predicted model accuracy can also use a classification matrix that calculates the
correct and incorrect value of the dependent variable. The classification matrix will
show the predictive strength of the regression model to predict the probability of
going concern firms. The results of classification are presented in Table 4.10 as
follows:
Table 4.10. Classification Tabel Classification Table
a,b
Observed
Predicted
Going Concern
Percentage
Correct
Non Going
Concern
Going
Concern
Step 0 Going Concern Non Going
Concern 0 9 .0
Going Concern 0 54 100.0
Overall Percentage 85.7
a. Constant is included in the model.
b. The cut value is .500
Source : Output SPSS 22
52
Based on Table Classification model step 0 above shows that from 63 companies
that are going concern property none of the companies predicted non going
concern. And 63 property companies are going concern among them 9 companies
predicted non going concern. So overall the accuracy of the model classification in
predicting proper going concern firms is 85.7% (54/63 * 100%). The high
percentage of accuracy of the classification table supports no significant difference
to the predicted data and observational data that shows as a good logistic regression
model.
E. Hypothesis Test
Hypothesis testing using logistic regression model. Logistic regression is used
to examine the effect of Company Size, Audit Quality, Audit Fees, and Tenure
Audit on going concern. To test the significance of the coefficient of each free
variable used p-value (probability value) with a significance level of 5% (0.05). If
the significant value is smaller than α = 0.05, then the regression coefficient is
significant.
53
Result hypothesis test present on table 4.11 as follows:
Table 4.11. Classification Table
Variables in the Equation
B S.E. Wald Df Sig. Exp(B)
Step 1a X1 1.349 .588 5.256 1 .022 3.853
X2(1) 3.693 1.669 4.899 1 .027 40.181
X3 1.226 .488 6.318 1 .012 .293
X4 -2.778 1.381 4.046 1 .044 .062
Constant 12.248 10.722 1.305 1 .253 208524.849
a. Variable(s) entered on step 1: X1, X2, X3, X4.
Source : Output SPSS 22
Based on Variables in the Equation model model step 1 shows the
calculation of coefficient value from the logistic regression model for each
independent variable, Wald Statistic, Significance and odds ratio (Exp (β)). And
from the table formed logistic regression equation is as follows:
( ) ( )
( )
Based on hypothesis testing table above shows that for Company Size
obtained beta value of correlation of 1.349 with significance of 0.0022. The
significance value less α = 0.05 indicates a significant influence of the Company
Size variable on Going Concern so that H1 is accepted. Exp Value (β) Company
54
Size (1) = 3.853 indicates that the probability of occurrence of one time a going
concern property prediction company is 3.853 times greater than that of a non-
going concern company. .
For variable independence of Quality Audit obtained beta value of correlation equal
to 3,693 with significance equal to 0,027. A significance value less than α = 0.05
indicates a significant influence of the Quality Audit variable on Going Concern so
that H2 is accepted. Thus it can be concluded that the higher the audit quality, the
tendency or probability for going concern is very high. Value Exp (β) Audit Quality
(1) = 40,181 indicates that the probability of occurrence of one time going concern
property prediction firm is 40,181 times bigger than in non-going concern
company.
For Audit Fees variable obtained value of correlation beta equal to 1,226
with significance equal to 0,012. A significance value that is less than α = 0.05
indicates a significant influence of the Fees Audit variable on Going Concern so
that H3 is accepted. Thus it can be concluded that the higher paid received, the
tendency probability of property companies for going concern is very high. Exp (β)
Audit Fees (1) = 0.293 indicates that the probability of occurrence of one time
going at property predicate firms is 0.293 times greater than in non-going concern
firms.
And for Tenure Audit variable obtained beta value of correlation of -2.778
with significance of 0.044. A significance value that is less than α = 0.05 indicates a
significant influence of the Tenure Audit variable on Going Concern so that H4 is
accepted. Thus it can be concluded that the lower paid received, the tendency of
55
probability for going concern is very high mean in auditing an auditor company
does not look at the high low fee provided but from professionalism. Exp (β)
Tenure Audit (1) = 0.062 indicates that the probability of occurrence of one time a
going concern property prediction company is 0.062 times greater than in a non-
going concern company.
56
Chapter V
Conclusion and Recommendation
A. Conclusion
Based on the analysis that has been done, it can be conclude as follows:
1. Significantly influences between company size variable to the Going
Concern with the significant score 0.022 and exp(β) = 3.853
2. Significantly influences between audit quality variable to the Going
Concern with the significant score 0.027 and exp(β) = 40.181
3. Significantly influences between audit fees variable to the Going Concern
with the significant score 0.012 and exp(β) = 0.293
4. Significantly influences between audit tenure variable to the Going Concern
with the significant score 0.44 and exp(β) = 0.062
B. Recommendation
1. For The Next Researchers
In order to gain deeper understanding about company size, audit
quality, audit tenure, audit fees, the next researchers is recommended to:
a. Enlarge the scope of research such as firm size, firm leverage and
financial performance, and use other variables to get various findings.
b. Enlarge the scope of research to other companies either from the same
sector or the same size that the finding could get generalized either for
the sector or the company size.
c. More different variable than previous research.
57
d. Use the other research methodology, for example using direct interview,
so the result will be more accurate.
2. For The Investor
The investor should be pay attention before they invest their money
to the company. It could be better if the company have more independent
commissioner to reduce asymmetry information and company collapse after
receiving going concern audit opinion.
58
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61
APENDIXES
Property Companies Name
No Code Company Name
1 APLN Agung Podomoro Land Tbk
2 ASRI Alam Sutera Reality Tbk
3 BAPA Bekasi Asri Pemula Tbk
4 BEST Bekasi Fajar Industrial Estate Tbk
5 BIPP Bhuawanatala Indah Permai Tbk
6 BKDP Bukit Darmo Property Tbk
7 BKSL Sentul City Tbk
8 BSDE Bumi Serpong Damai Tbk
9 BDY Buku Danayaksa
10 COWL Cowell Development Tbk
11 CTRA Ciputra Development Tbk
12 DART Duta Anggada Realty Tbk
13 DILD Intiland Development Tbk
14 DUTI Duta Pertiwi Tbk
15 ELTY Bakrieland Development Tbk
16 EMDE Megapolitan Development Tbk
17 FMII Fortune Mate Indonesia Tbk
18 GAMA Gading Development Tbk
19 GMTD Goa Makassar Tourism Development Tbk
20 GPRA Perdana Gapura Prima Tbk
22 GWSA Greenwood Sejahtera Tbk
62
Attachment 1: Raw Data
Company Size (X1), Audit Quality (X2), Audit Fees (X4), Audit Tenure (X4)
Going Concern (Y)
No
Company
Property
Name
Year Company Size Company Size
Ln(Compa
ny Size)
Audit
Quality Audit Fees Audit Fees
Ln(Aud
it Fees)
Audit
Tenure
Going
Concer
n
(X1) (X1) in Million (X1) (X2) (X3)
(X3) In
Million (X3) (X4) (Y)
1 APL 2013
19,679,415,197
19,679,415.20
16.80 1
8,824,863
8,824,863
16 116 1
2014
23,685,737,844
23,685,737.84
16.98 1
11,009,926
11,009,926
16 118 1
2015
24,559,174,988
24,559,174.99
17.02 1
9,734,222
9,734,222
16 118 1
2 ASRI 2013
14,428,082,567
14,428,082.57
16.48 0
20,631,149
20,631,149
17 111 1
2014
3,188,091,155
3,188,091.16
14.97 0
24,954,336
24,954,336
17 96 1
2015
2,698,917,559
2,698,917.56
14.81 0
12,501,034
12,501,034
16 119 1
3 BAPA 2013
175,635,233,972
175,635,233.97
18.98 0
941,847,448
941,847,448
21 114 1
2014
176,171,620,663
176,171,620.66
18.99 0
382,989,186
382,989,186
20 113 1
2015
175,743,601,667
175,743,601.67
18.98 0
480,589,409
480,589,409
20 91 1
4
BEST
LKT 2013
3,360,272,281,414
336,027,228.14
19.63 0
1,061,605,000
1,061,605.00
14 116 1
2014
3,652,993,439,542
365,299,343.95
19.72 0
9,328,633,562
9,328,633.56
16 110 1
2015 0 114 1
63
4,631,315,439,422 463,131,543.94 19.95 10,296,256,721 10,296,256.72 16
5 BIIP 2013
43,968,751,897
43,968,751.90
17.60 0
89,895,561
89,895.56
11 192 1
2014
51,767,454,439
51,767,454.44
17.76 0
1,017,894,378
1,017,894.38
14 162 1
2015
124,366,098,795
124,366,098.80
18.64 0
1,515,956,180
1,515,956.18
14 114 1
6 BKDP 2013
845,487,178,846
845,487,178.85
20.56 0
1,007,035,714
1,007,035.71
14 115 1
2014
829,193,049,942
829,193,049.94
20.54 0
1,229,900,000
1,229,900.00
14 113 1
2015
791,161,825,436
791,161,825.44
20.49 0
1,963,627,272
1,963,627.27
14 118 1
7 BKSL 2013
10,654,200,606,913
106,542,006.07
18.48 0
32,492,574,146
3,249,257.41
15 105 1
2014
9,986,973,579,779
99,869,735.80
18.42 0
8,893,032,015
8,893,032.02
16 109 1
2015
11,145,896,809,593
111,458,968.10
18.53 0
3,282,653,656
3,282,653.66
15 114 1
8 BSDE 2013
22,572,292,483,511
225,722,924.84
19.23 0
4,520,544,225
4,520,544.23
15 76 1
2014
28,206,859,159,578
282,068,591.60
19.46 0
52,780,808,294
5,278,080.83
15 71 1
2015
36,022,148,489,646
360,221,484.90
19.70 0
97,559,160,214
97,559,160.21
18 74 1
9
Buku
Danayaksa 2013
5,551,173,684
5,551,173.68
15.53 0
923,224,000
923,224,000
21 106 0
2014
5,570,748,962
5,570,748.96
15.53 0
809,125,000
809,125,000
21 110 0
2015
5,566,425,030
5,566,425.03
15.53 0
69,295,000
69,295,000
18 114 1
10 COWL 2013
1,944,913,754,306
194,491,375.43
19.09 0
175,000,000
175,000,000
19 114 1
2014
3,682,393,492,170
368,239,349.22
19.72 0
11,111,941,189
11,111,941.19
16 117 1
64
2015
3,540,585,749,217
354,058,574.92
19.68 0
5,553,087,970
5,553,087.97
16 117 1
11 CTRA 2013
20,245,534,912,143
20,245,535
16.82 1
24,500,498,181
24,500,499
17 83 1
2014
23,538,715,238,878
23,538,716
16.97 1
5,755,712,381
57,557,124
18 83 1
2015
26,258,718,560,250
26,258,719
17.08 1
24,500,498,181
24,500,499
17 83 1
12 DART 2013
4,768,449,638
4,768,450
15.38 1
76,500,498,191
76,500,498
18 88 0
2014
5,114,273,658
5,114,274
15.45 1
5,117,016
5,117,016
15 88 0
2015
5,739,863,241
5,739,864
15.56 1
9,837,084
9,837,084
16 88 0
13 DILD 2013
1,306,185,456,742
13,061,855
16.39 0
6,736,515,120
67,365,152
18 89 1
2014
2,468,562,684,275
24,685,627
17.02 0
8,906,064,879
89,060,649
18 89 1
2015
2,925,607,417,725
29,256,075
17.19 0
15,885,968,697
158,859,687
19 89 1
14 DUTI 2013
7,473,827,304,875
74,738,274
18.13 0
18,950,030,437
189,500,305
19 43 1
2014
8,130,786,587,766
81,307,866
18.21 0
62,389,844,181
623,898,442
20 43 1
2015
9,014,911,216,451
90,149,113
18.32 0
62,092,285,232
620,922,853
20 43 1
15 ELTY 2013
12,302,355,756,665
123,023,558
18.63 0
31,250,467,933
312,504,679
20 153 1
2014
8,130,786,587,766
81,307,866
18.21 0
66,294,958,118
666,294,959
20 118 0
2015
9,014,911,216,451
90,149,113
18.32 0
22,284,473,498
222,844,735
19 243 1
16 EMDE 2013
938,536,950,089
9,385,369
16.05 0
2,926,977,450
29,269,775
17 87 1
2014 0 87 1
65
1,179,018,690,672 11,790,187 16.28 4,760,389,661 47,603,897 18
2015
1,196,040,969,781
11,960,409
16.30 0
2,658,133,510
26,581,336
17 87 1
17 FMII 2013
429,979,371,876
4,299,794
15.27 0
516,729,426
5,167,295
15 82 1
2014
459,446,166,179
4,594,462
15.34 0
369,977,443
3,699,775
15 82 1
2015
584,000,536,156
5,840,006
15.58 0
163,374,126
1,633,742
14 82 1
18 GAMA 2013
1,290,583,599,639
12,905,836
16.37 1
514,176,335
5,141,764
15 87 1
2014
1,390,092,733,576
13,900,928
16.45 1
1,169,878,691
11,698,787
16 87 1
2015
1,336,562,720,363
13,365,628
16.41 1
867,115,000
8,671,150
16 87 1
19 GMTD 2013
1,307,819,055,774
12,078,191
16.31 0
665,050,000
6,650,500
16 50 1
2014
1,524,241,388,731
15,242,414
16.54 0
1,044,605,752
10,446,058
16 50 1
2015
1,273,990,253,786
12,739,903
16.36 0
1,815,745,581
18,157,456
17 50 1
20 GPRA 2013
1,332,678,268,231
13,326,783
16.41 1
2,322,854,493
23,228,545
17 87 0
2014
1,517,576,344,888
15,175,764
16.54 1
2,387,738,404
23,877,385
17 87 0
2015
1,574,174,572,164
15,741,746
16.57 1
7,048,356,490
70,483,565
18 87 0
21 GWSA 2013
4,688,677,189,263
46,886,678
17.66 1
5,034,216,219
50,342,163
18 88 1
2014
5,340,991,746,366
5,340,992
15.49 1
3,647,344,547
36,473,446
17 88 1
2015
6,805,277,762,308
6,805,278
15.73 1
4,535,655,066
45,356,551
18 88 1
66
Company Size (X1),
Audit Quality (X2), Audit Fees (X4), Audit Tenure (X4),
Going Concern (Y) using SPSS 22
Descriptives
Notes
Output Created 21-JUN-2017 20:07:22
Comments
Input Data D:\data delia logistik\data desk.sav
Active Dataset DataSet2
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data
File 63
Missing Value Handling Definition of Missing User defined missing values are
treated as missing.
Cases Used All non-missing data are used.
Syntax DESCRIPTIVES VARIABLES=X1 X2
X3 X4 Y
/STATISTICS=MEAN STDDEV MIN
MAX.
Resources Processor Time 00:00:00.00
Elapsed Time 00:00:00.00
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
Company Size(X1) 63 2698917559 36022148489646 4884372725620.64 7834966869052.086
Audit Quality 63 .00 1.00 .2857 .45538
Audit Fees 63 5117016 97559160214 11366435222.11 20982173140.182
Audit Tenure 63 43.00 243.00 99.0952 32.25089
Going Concern 63 .00 1.00 .8571 .35274
Valid N (listwise) 63
67
Attachment 3: Result testing Logistic Variable: Company Size (X1),
Audit Quality (X2), Audit Fees (X4), Audit Tenure (X4),
Going Concern Y using SPSS 22
LOGISTIC REGRESSION VARIABLES Y
/METHOD=ENTER X1 X2 X3 X4
/CONTRAST (X2)=Indicator
/CLASSPLOT
/PRINT=GOODFIT CORR ITER(1)
/CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).
Logistic Regression
Notes
Output Created 21-JUN-2017 16:21:32
Comments
Input Data D:\data delia logistik\data delia7.sav
Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data File 63
Missing Value Handling Definition of Missing User-defined missing values are treated as
missing
Syntax LOGISTIC REGRESSION VARIABLES Y
/METHOD=ENTER X1 X2 X3 X4
/CONTRAST (X2)=Indicator
/CLASSPLOT
/PRINT=GOODFIT CORR ITER(1)
/CRITERIA=PIN(0.05) POUT(0.10)
ITERATE(20) CUT(0.5).
Resources Processor Time 00:00:00.03
Elapsed Time 00:00:00.03
68
Case Processing Summary
Unweighted Casesa N Percent
Selected Cases Included in Analysis 63 100.0
Missing Cases 0 .0
Total 63 100.0 Unselected Cases 0 .0 Total 63 100.0
a. If weight is in effect, see classification table for the total number of cases.
Dependent Variable Encoding
Original Value Internal Value
Non Going Concern 0 Going Concern 1
Categorical Variables Codings
Frequency
Parameter coding
(1)
Audit Quality Non Big Four 45 1.000
Big Four 18 .000
Block 0: Beginning Block
Iteration Historya,b,c
Iteration -2 Log likelihood
Coefficients
Constant
Step 0 1 52.783 1.429
2 51.687 1.752
3 51.675 1.791
4 51.675 1.792
a. Constant is included in the model. b. Initial -2 Log Likelihood: 51.675 c. Estimation terminated at iteration number 4 because parameter estimates changed by less than .001.
Classification Table
a,b
Observed
Predicted
Going Concern
Percentage Correct
Non Going Concern Going Concern
Step 0 Going Concern Non Going Concern 0 9 .0
Going Concern 0 54 100.0
Overall Percentage 85.7
a. Constant is included in the model. b. The cut value is .500
69
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 0 Constant 1.792 .360 24.766 1 .000 6.000
Variables not in the Equation
Score df Sig.
Step 0 Variables X1 6.844 1 .009
X2(1) 7.467 1 .006
X3 3.828 1 .050
X4 4.955 1 .026
Overall Statistics 19.059 4 .001
Block 1: Method = Enter
Iteration Historya,b,c,d
Iteration -2 Log likelihood
Coefficients
Constant X1 X2(1) X3 X4
Step 1 1 40.146 5.988 .175 .786 -.184 -1.091
2 31.091 8.242 .439 1.390 -.395 -1.723
3 26.278 8.896 .825 2.173 -.710 -2.086
4 24.490 10.418 1.174 3.074 -1.033 -2.469
5 24.256 11.865 1.326 3.584 -1.196 -2.724
6 24.251 12.233 1.348 3.690 -1.225 -2.776
7 24.251 12.248 1.349 3.693 -1.226 -2.778
8 24.251 12.248 1.349 3.693 -1.226 -2.778
a. Method: Enter b. Constant is included in the model. c. Initial -2 Log Likelihood: 51.675 d. Estimation terminated at iteration number 8 because parameter estimates changed by less than .001.
Omnibus Tests of Model Coefficients
Chi-square df Sig.
Step 1 Step 27.424 4 .000
Block 27.424 4 .000
Model 27.424 4 .000
Model Summary
Step -2 Log likelihood Cox & Snell R
Square Nagelkerke R
Square
1 24.251a .353 .631
a. Estimation terminated at iteration number 8 because parameter estimates changed by less than .001.
Hosmer and Lemeshow Test
Step Chi-square df Sig.
1 2.108 8 .978
70
Contingency Table for Hosmer and Lemeshow Test
Going Concern = Non Going Concern Going Concern = Going Concern
Total Observed Expected Observed Expected
Step 1 1 5 4.963 1 1.037 6
2 3 2.343 3 3.657 6
3 0 .797 6 5.203 6
4 1 .517 5 5.483 6
5 0 .244 6 5.756 6
6 0 .098 6 5.902 6
7 0 .032 6 5.968 6
8 0 .005 6 5.995 6
9 0 .001 6 5.999 6
10 0 .000 9 9.000 9
Classification Table
a
Observed
Predicted
Going Concern
Percentage Correct Non Going Concern Going Concern
Step 1 Going Concern Non Going Concern 5 4 55.6
Going Concern 3 51 94.4
Overall Percentage 88.9
a. The cut value is .500
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 1a X1 1.349 .588 5.256 1 .022 3.853
X2(1) 3.693 1.669 4.899 1 .027 40.181
X3 -1.226 .488 6.318 1 .012 .293
X4 -2.778 1.381 4.046 1 .044 .062
Constant 12.248 10.722 1.305 1 .253 208524.849
a. Variable(s) entered on step 1: X1, X2, X3, X4.
Correlation Matrix
Constant X1 X2(1) X3 X4
Step 1 Constant 1.000 -.346 .541 -.480 -.527
X1 -.346 1.000 .203 -.488 -.296
X2(1) .541 .203 1.000 -.684 -.366
X3 -.480 -.488 -.684 1.000 .250
X4 -.527 -.296 -.366 .250 1.000