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The Influence of Pentagon Fraud on The Financial Statements of
Infrastructure Companies Listed in Indonesia Stock Exchange
Emylia Yuniarti, Rela Sari, Nilam Kesuma, and Fitri Damayani
Accounting Department, Faculty of Economics, Universitas Sriwijaya, Palembang, Indonesia
Keywords: Financial statement fraud, pentagon fraud, fraud score model
Abstract: The purpose of this research is to examine empirically the influence of fraud pentagon on financial
statement fraud. Independent variables that used in this research are financial stability, financial target,
external pressure, managerial ownership, ineffective monitoring, nature of industry, change in auditor,
change in directors, and frequent number of CEO’s picture. Dependent variable is financial statement fraud.
Populations on this research are infrastructure companies that listed in Indonesian Stock Exchange (IDX)
during 2015-2017. By using purposive sampling method, there are 81 samples. The statistical method is
multiple linier regression analysis, with hypotheses testing of statistic t-tests, statistic F-tests, and coefficient
of determination. The result of this research shows that nature of industry has significant influence on
financial statement fraud. Whereas the other independent variables have no influence on financial statement
fraud. Simultaneous test result shows that independent variables simultaneously have influence on financial
statement fraud.
1 INTRODUCTION
Financial statements are summaries from
recording process and financial transactions which
occured during a certain period (Listyawati, 2016).
According to Indonesian financial accounting
standards No.1, the purpose of financial statements
is to provide information about financial position,
performance, and changes in financial position of an
entity that is beneficial to a large number of users in
making ekonomic decisions. These users can assess
the company’s performance through its financial
statement. Therefore, companies sometimes commit
acts of fraud to the financial statements in order their
performance gets a good assessment.
Financial statement fraud is a deliberate attempt
by companies to deceive and mislead users,
especially investors and creditors, by presenting and
falsifying the material value of financial statements
(Sihombing & Rahardjo, 2014). Fraud in financial
statements causes that financial statements become
not reliable due to dishonest presentation and there
are some factors that mislead the users in making
decision.
Fraud in Indonesia can take place in various
sectors such as public companies that often involved
in government procurement project. According to
kompas.com, government procurement of goods and
services project is the biggest area to commit fraud
like corruption. Almost 80 percent cases that
handled by Komisi Pemberantasan Korupsi (KPK)
are from that area. The companies that often
involved in that area are listed companies in
infrastructure sector like construction,
transportation, and telecommunication. A lot of
companies in those sectors have been classified as
blacklist in Lembaga Kebijakan Pengadaan Barang
dan Jasa Pemerintah (LKPP) (Aprillia et al., 2015).
If those companies commit fraud in their operation
activities, it doesn’t rule out the possibility that fraud
can be happened in their financial statements.
Survey from Association of Certified Fraud
Examiners (ACFE) at 2014 also showed that one of
those sectors, that is construction, is the most
frequent sector which commit financial statement
fraud.
One of theory that can be used to detect fraud is
fraud pentagon theory which developed by Jonathan
Marks. Five elements in this theory are pressure,
opportunity, rationalization, competence, and
arrogance.
Yuniarti, E., Sari, R., Kesuma, N. and Damayani, F.
The Influence of Pentagon Fraud on The Financial Statements of Infrastructure Companies Listed in Indonesia Stock Exchange.
DOI: 10.5220/0008442705730583
In Proceedings of the 4th Sriwijaya Economics, Accounting, and Business Conference (SEABC 2018), pages 573-583
ISBN: 978-989-758-387-2
Copyright
c
 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
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2 LITERATURE REVIEW
2.1 Agency Theory
Iqbal & Murtanto (2016) explain that agency
theory describes the relation between shareholder as
principal and management as agent. Management is
a party contracted by shareholders to work for their
interests. Therefore, management has to account the
performance to shareholders.
In company, management has authority in
making decision about certain matters that can affect
the condition of company. However, such decision
making sometimes is incompatible with the interests
of shareholders. This difference of interest causes
conflict of interest between the two parties so that
the company as an agent faces various conditions
that make them committing fraud (Sihombing &
Rahardjo, 2014).
One of media that can be used by management to
commit fraud is financial statements. The financial
statements serve as an intermediary between
management and shareholders regarding the
company’s performance through financial
information. Fraud pentagon theory can be a tool to
detect financial statement fraud performed by
management.
2.2 Financial Statement Fraud
Financial statement fraud is a deliberate attempt
by companies to deceive and mislead users,
especially investors and creditors, by presenting and
falsifying the material value of financial statements
(Sihombing & Rahardjo, 2014). According to
Aprilia (2017), financial statement fraud is
fraudulent by management of company in the form
of material misstatements in financial statements
presented by them and this is detrimental to
investors and other interested parties.
2.3 Fraud Pentagon Theory
Fraud Pentagon is one of theoryies that explain
the condition that cause fraud. This theory is
development of fraud triangle proposed by Cressey.
Fraud triangle consists of three elements namely
pressure, opportunity, and rationalization. This
theory was later developed by Jonathan Marks in
2009 (Vassiljev & Alver, 2016). There are two
additional elements that are incorporated into fraud
pentagon, those are competence and arrogance. The
representation of fraud pentagon theory is as
follows.
Figure 1: Crowe’s Fraud Pentagon Theory.
These are the explanation about those five
elements.
a. Pressure
Harahap et al (2017) explain that pressure is the
encouragement of the person who commit fraud.
Pressure can include almost everything like
lifestyle, economic demand, and financial or non
financial matters. One of pressure for company
or management to manipulate its financial
statement is when there is decline in financial
prospect (Elder et al., 2013).
b. Opportunity
Opportunity is the condition that give a chance
for management or employee to commit fraud
(Elder et al., 2013), such as boards of directors or
audit committees that are not effective in
overseeing financial reporting so that opportunity
arise.
c. Rationalization
Rationalization is a justification that arises in the
mind of management when fraud has occurred.
This thought will arise because they do not want
their action to be known so that they justify the
manipulation that has been done. This action is
done to keep them safe and free from punishment
(Aprilia, 2017).
d. Competence
Competence is an employee’s ability to override
internal controls, develop a sophisticated
concealment strategy, and to control the social
situation to his or her advantage by selling it to
others. (Crowe Horwarth, 2012). In short, Aprilia
(2017) explain that competence is management
or employee ability to go through the internal
control.
e. Arrogance
Arrogance is an attitude of superiority and
entitlement or greed on the part of a person who
believes that internal controls simply do not
Pressure
Crowe’s Fraud
Pentagon
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personally apply (Crowe Horwarth, 2012).
Arrogance is also a boastful attitude from
someone who believes he or she is capable to
commit fraud and will not be known when fraud
has occurred (Aprilia, 2017).
2.4 Fraud Score Model
Fraud Score Model or F-Score consists of
description of data presented from the sum of
accrual quality and financial performance. The sum
of these two components can well predict the risk of
financial statement fraud seen from financial
statement perspective (Rini & Ahmad, 2012).
Accrual quality can be proxied with RSST
accrual created by Richardson, Sloan, Soliman, and
Tuna. RSST can describe all non-cash and non-
equity changes in company’s balance sheet as
accrual. Rini & Ahmad (2012) explain that accrual
basis in recording financial statements provides a lot
of flexibility for management to manipulate the
financial statements using discretionary accrual, ie
free accrual recognition, unregulated, and base on
management policy.
While financial performance is used to examine
whether managers misstate their financial statements
to mask deteriorating performance (Dechow et al.,
2010). Financial performance consists of change in
receivable, change in inventory, change in cash
sales, and change in earnings.
2.5 Research Framework
This research uses fraud pentagon theory to
detect financial statement fraud in a company. There
are five elements of fraud pentagon, ie pressure,
opportunity, rationalization, competence, and
arrogance. Pressure can be proxied with financial
stability, financial target, external pressure, and
managerial ownership. There are two proxies for
opportuniy, those are ineffective monitoring and
nature of industry. Rationalization is proxied with
change in auditor. Competence is proxied with
change in directors. The last is arrogance that can be
proxied with frequent number of CEO’s Picture. The
following below is research framework based on the
expalantion above.
Figure 2: Research Framework
2.6 Research Hypothesis
2.6.1 Financial Stability In Influencing
Financial Statement Fraud
According to SAS No. 99, managers face
pressure to commit financial statement fraud when
financial stability and/or profitability are threatened
by economic, industry, or entity operating conditions
(Skousen et al., 2008). Tessa & Harto (2016) explain
that the amount of total assets owned by company
become the main attraction for investors, creditors,
and other decision makers. When the total assets is
quite a lot, the company is considered capable of
providing the maximum return for investors.
The fraudulent that occurs for getting the well
seen financial stability is by manipulating the wealth
of assets in financial statements. The ratio of change
in total assets can be used to see an increase in the
company’s assets wealth. The research result of
Iqbal & Murtanto (2016) showed that financial
stability affects the financial statement fraud which
is the greater ratio the greater possibility of financial
statement fraud. Based on description above, the
PRESSURE
• Financial
Stability (X
1
)
• Financial
Target (X
2
)
•
External
Pressure (X
3
)
OPPORTUNITY
• Ineffective
Monitoring
(X
5
)
• Nature of
RATIONALIZATI
ON
• Change in
Auditor (X
7
)
COMPETENCE
• Change in
Directors (X
8
)
ARROGANCE
• Frequent
Number of
CEO’s Picture
(X
9
)
Financial
Statement
Fraud (Y)
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first hypothesis is: H
1
: Financial stability has
significant effect on financial statement fraud.
2.6.2 Financial Target In Influencing
Financial Statement Fraud
Management has a pressure to reach the financial
target that has been planned before. However,
sometimes there are inhibiting factors for the
management to achieve financial target so that it
cannot be fulfilled. Pressure to achieve this target
can lead to fraudulent management action to achieve
financial target and maintain financial performance
to look good. The company's financial target is
usually earnings that can be seen from return on
assets (ROA) (Tessa & Harto, 2016). ROA is used to
indicate how efficiently an asset has been used.
ROA is also often used in assessing the performance
of managers and determining bonus, wage increases,
and others. Therefore, management will attempt to
manipulate financial statements such as profit
manipulation to be considered capable of achieving
predetermined financial targets and get a big bonus.
Then the second hypothesis is:
H
2
: Financial target has significant effect on
financial statement fraud.
2.6.3 External Pressure In Influencing
Financial Statement Fraud
External pressure can be proxied by using
leverage ratio (LEV) i.e. The ratio between total
liabilities and total assets. Tessa & Harto (2016)
explain that companies with high leverage ratio are
considered to have large debts and high credit risk.
This makes creditors hesitant and worried about
lending to them. Thus, the companies try to make
creditors believe that they are able to repay the loan
by manipulating. The research result of Tiffani &
Marfuah (2015) showed a significant positive effect
on financial statement fraud. This means that the
greater pressure from external parties will increase
the potential for management to commit financial
statement fraud. Based on the explanation, the third
hypothesis is:
H
3
: External pressure has significant effect on
financial statement fraud.
2.6.4 Managerial Ownership in Influencing
Financial Statement Fraud
Tiffani & Marfuah (2015) explain that the
ownership of shares by management makes them
feel they have a claim right on the income and assets
of the company so that it will affect the company's
financial condition. Ownership of shares by
management leads them to use the company's funds
for personal interest. Personal interest that is the
pressure experienced by the management encourages
the occurrence of fraudulent financial statements.
The higher percentage of shares ownership by
management the higher risk of financial statement
fraud can occur. Based on the explanation, the fourth
hypothesis is:
H
4
: Managerial ownership has significant effect on
financial statement fraud.
2.6.5 Ineffective Monitoring In Influencing
Financial Statement Fraud
Ineffective monitoring is a condition where there
is no effective internal control system owned by the
company (Tessa & Harto, 2016). Management can
commit fraudulent actions due to opportunities
resulting from inadequate monitoring or ineffective
internal control system. Independent board of
commissioners are believed to increase the
company’s monitoring effectiveness. Thus, a
company with small number of board of
commissioners will lead to higher fraud. According
to the explanation, the fifth hypothesis is:
H
5
: Ineffective monitoring has significant effect on
financial statement fraud.
2.6.6 Nature Of Industry In Influencing
Statement Fraud
Tiffani & Marfuah (2015) explain that there are
certain accounts in the financial statements which
balances are determined by the company based on
an estimate, such as uncollected receivable account.
This is where an opportunity can arise to commit
financial statement fraud. Research conducted by
Sihombing & Rahardjo (2014) shows that nature of
industry proxied by change in receivable ratio
influence financial statements fraud significantly.
They explain that an increase in the amount of
receivable from the previous year can be an
indication that the company's cash flow is not good.
The number of receivable owned by the company
will reduce the amount of cash that the company can
use for its operational activities. Limited cash can be
an encouragement for management to manipulate
financial statements. Based on the description, the
sixth hypothesis is:
H
6
: Nature of industry has significant effect on
financial statement fraud.
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2.6.7 Change In Auditor In Influencing
Financial Statement Fraud
Change in auditor can be considered as a form to
remove the fraud trail found by the previous auditor.
This tendency encourages companies to replace their
independent auditor to cover up the fraud within the
company (Tessa & Harto, 2016). Not only to remove
traces of fraud, if company begins to be dissatisfied
with the performance of auditor that cannot be
intervened or influenced to manipulate the audit
results, the fraud tendency will be higher (Stice,
1991 in Sihombing & Rahardjo, 2014). On this
basis, the seventh hypothesis is:
H
7
: Change in auditor has significant effect on
financial statement fraud.
2.6.8 Change in Directors In Influencing
Financial Statement Fraud
The change in directors is not always good for
the company. A change in board of directors can be
an attempt to get rid of the directors who are deemed
to know the company's fraud (Devy et al., 2017). In
addition, more competent directors can make fraud
more likely to happen. Wolfe & Hermanson (2004)
explain that fraudulent can occur if done by
someone with the right ability to carry out the fraud.
Employees who have a certain intellect or ability are
considered capable of identifying opportunities and
committing acts of fraud in accordance with their
abilities. Therefore, the replacement of new directors
who are more competent is considered capable of
committing acts of fraud. Thus, the eighth
hypothesis is:
H
8
: Change in directors has significant effect on
financial statement fraud.
2.6.9 Frequent Number Of CEO’s Picture in
Influencing Financial Statement Fraud
Arrogance is an attitude of superiority and
entitlement or greed on the part of a person who
believes that internal controls simply do not
personally apply (Crowe Horwarth, 2012). Tessa &
Harto (2016) explain that the number of CEO’s
pictures emblazoned in the company's annual report
can present the level of arrogance or superiority that
CEO has. Yusof et al (2015) also explain that the
number of pictures show the way CEOs to be known
to the wide community and treat themselves as
celebrity because of their arrogant nature. This is
consistent with the explanation of Crowe Horwart
(2011) which mentions that one of character in
arrogance is to have big ego - CEO as celebrity -
factor of pride. Therefore, more and more CEO’s
pictures in the annual report allegedly will make the
arrogance higher so that he/she is able to commit
fraud without fear of internal control. Based on the
explanation, the ninth hypothesis is:
H
9
: Frequent number of CEO’s picture has
significant effect on financial statement fraud.
3 RESEARCH METHODOLOGY
3.1 Population and Sample
This study is a quantitative descriptive research
that reveals the magnitude of an influence or
relationship between variables expressed in
numbers. This study uses infrastructure companies
taken from construction, transportation, utilities and
infrastructure sectors listed on Indonesia Stock
Exchange 2015-2017. The data source in this
research is secondary data, ie annual reports
obtained from Indonesia Stock Exchange website
(www.idx.co.id) and the company's official website.
The population numbers are 74 companies.
Sampling technique used is purposive sampling. The
criteria used in the sampling of this study are:
a. The infrastructure companies listed on Indonesia
Stock Exchange during 2015 - 2017.
b. Companies that publish annual report that have
been audited in the company's website or BEI
website during 2015 - 2017 stated in Rupiah
(Rp).
c. The Companies are not delisted during 2015 -
2017.
d. The Companies have complete data relating to
research variables (all datas are available in
publication during 2015 - 2017).
e. The companies provide complete datas of
20154to be used as a comparison in 2015.
Based on those criteria, total samples that will be
used are 27 companies with three years observation
period.
3.2 Variable Operationaliazation
3.2.1 Dependent Variable
Dependent variable in this study is financial
statement fraud measured by F-Score model. F-
Score model is the sum of two variables: accrual
quality and financial performance. Accrual quality is
proxies with RSST accrual, while financial
performance is proxied with changes in receivable,
The Influence of Pentagon Fraud on The Financial Statements of Infrastructure Companies Listed in Indonesia Stock Exchange
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changes in inventory, changes in cash sales, and
changes in earnings (EBIT).
𝐑𝐒𝐒𝐓$𝐀𝐜𝐜𝐫𝐮𝐚𝐥 =
𝚫𝐖𝐂 + $𝚫𝐍𝐂𝐎 + $𝚫𝐅𝐈𝐍
𝐀𝐯𝐞𝐫𝐚𝐠𝐞$𝐓𝐨𝐭𝐚𝐥$𝐀𝐬𝐬𝐞𝐭𝐬
WC (Working Capital)
=
(Current Assets – Cash and Short term
Investments) – (Current Liabilities – Debt in
Current Liabilities)
NCO (Non-Current Operating)
=
(Total Assets – Current Assets – Invesment and
Advances) – (Total Liabilities – Current Liabilities
– Long Term Debt)
FIN (Financial Accrual)
=
(Short Term Investment + Long Term Investment)
– (Short Term Debt + Long Term Debt)
ATS (Average Total Assets)
=
Beginning$Total$Assets + End$Total$Assets
2
Financial performance = change in receivable + change
in inventories + change in cash sales + change in
earnings
Change in
receivables
=
ΔReceivables
Average$Total$Assets
Change in
inventories
=
ΔInventories
Average$Total$Assets
Change in
cash sales
=
ΔSales
Sales$(t)
− $
ΔReceivables
Receivables$(t)
Change in
earning
=
Earnings$(t)
Average$Total$Assets$(t)
− $
Earnings$(t − 1)
Average$Total$Assets$(t − 1)
3.2.2 Independent Variables
Variable
Operational Variable Definition
Financial
Stability
(ACHANGE)
ACHANGE
=
(Total$Assets
Y
$– $Total$Assets
$Y[\
)
$Total$Aset
Y
Financial
Target (ROA)
ROA =
Net$Income
Total$Assets
External
Pressure
(LEV)
LEV =
Total$Liabilities
Total$Assets
Managerial
Ownership
(OSHIP)
OSHIP =
Total$Managerial$Shares
Total$Number$of$Shares
Ineffective
Monitoring
(BDOUT)
BDOUT
=
The$Number$of$Independent$Board$of$Commissioners
Total$Board$of$Commissioners
Nature of
Industry
(RECEIVAB
LE)
RECEIVABLE
= $
Receivable
Sales
− $
Receivable$(t − 1)
Sales$(t − 1)
Change in
Auditor
Change in auditor is dummy
variable. This variable is coded 1 if
there is change of Public Accounting
Firm during 2014 - 2016, and code 0
otherwise.
Change in
Directors
Change in directors is dummy
variable. This variable is coded 1 if
there is change of director during
2014 - 2016, and code 0 otherwise.
Frequent
Number of
CEO’s
Picture
This variable uses the number of
CEO’s pictures present in annual
report during 2014 - 2016.
3.3 Data Analysis Methode
This research begins with descriptive statistic
and classical assumption test consisting of normality
test, multicollinearity test, autocorrelation test, and
heteroscedasticity test, then hypothesis testing will
be done. The regression equation used in this
research is as follows:
F-Score = ß0 + ß1ACHANGE + ß2ROA + ß3LEV +
ß4OSHIP + ß5BDOUT +
ß6RECEIVABLE + ß7AUDCHANGE +
ß8DCHANGE + ß9CEOPIC + ε
F-Score
=
Financial statement fraud
ß0
=
Constant
ß1,2,3,4,5,6,7,8,9
=
Regression coefficient
ACHANGE
=
Change in total assets ratio
ROA
=
Net income per total assets ratio
LEV
=
Total liabilities per total assets
ratio
OSHIP
=
Managerial ownership ratio
BDOUT
=
Independent board of
commisioners ratio
RECEIVABLE
=
Change in receivables ratio
AUDCHANGE
=
Change in auditor
DCHANGE
=
Change in directors in company
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CEOPIC
=
The number of CEO’s picture in
annual report
ε
=
Error
4 DATA ANALYSIS AND
DISCUSSION
4.1 Descriptive Statistic
Descriptive statistical analysis is used to provide
an overview of the minimum, maximum, mean, and
standard deviation of each research variable. The
results of descriptive statistical analysis are
presented in the following table.
Based on Table 4.1, it can be seen that the
average value of dependent variable (financial
statement fraud) which measured by F-Score is 0,
0448 indicates the average level of financial
statement fraud that occur in infrastructure
companies. Company with the lowest risk of
financial statement fraud is PT Arpeni Pratama
Ocean Line Tbk. in 2015 with a minimum value of -
1,2061 and the highest risk of financial statement
fraud is PT Leyand International Tbk. in 2016 with a
maximum value of 1,6432.
Table 4.1: Descriptive Statistic
N
Min
Max
Mean
Std. Dev
F-Score
81
-1,206
1,6432
,04481
,42416
ACHANGE
81
-,3871
,5861
,08387
,18488
ROA
81
-,4891
,2126
,03096
,09957
LEV
81
,0392
5,3653
,68304
,75505
OSHIP
81
,0000
,6640
,03579
,12577
BDOUT
81
,2500
,6667
,41053
,10594
RECEIV
81
-,0875
,3816
,02140
,07897
AUDCHANGE
81
0
1
,16
,369
DCHANGE
81
0
1
,38
,489
CEOPIC
81
0
26
5,01
4,440
Valid N (listwise)
81
4.2 Classical Assumption Test
The result of normality test using the
Kolmogorov-Smirnov test above shows a
significance value of 0,226. The value is greater than
0,05 so it can be concluded that the data tested in
this study is normally distributed. The result of
multicollinearity test shows that all tolerance values
are more than 0,10 and VIF values less than 10 so it
can be concluded that there is no correlation
between independent variables or no
multicollinearity problem in the data tested in this
study. Result of Autocorrelation Test test result
shows a significance value of 0,577. This value is
greater than 0,05 so it can be concluded that there is
no autocorrelation problem in the data tested in this
study.
It can be seen from the picture that:
a. The data dots spread above and below or around
0.
b. Data dots do not gather just above or below only.
c. The spread of data dots does not form a wavy
pattern widened then narrowed and widened
again.
d. The distribution of data dots is not patterned.
Thus, it can be concluded that there is no
heteroscedasticity on the data tested in this study.
The result of classical assumption test consisting of
normality test, multicollinearity test, autocorrelation
test, and heteroscedasticity test show there are no
problems in data normality, multicollinearity,
autocorrelation, and heteroscedasticity so that the
data in this research can be used in multiple
regression analysis.
4.3 Hypothesis Test
4.3.1 Simultaneous Regression Coefficient
(F Test)
This test aims to show how far the influence of
independent variables individually explain the
dependent variable. The result of f test can be seen
in the table 4.2 following. This test aims to test
whether the independent variables affect the
dependent variable simultaneously. The result of F
test is presented in following table.
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Tabel 4.2: Hasil Uji Statistik F.
Model
Sum of
Square
s
Df
Mean
Square
F
Sig.
Regression
7,783
9
,865
9,289
,000
b
Residual
6,610
71
,093
Total
14,393
80
All independent variables are said to affect the
dependent variable simultaneously if the value of F
arithmetic > F table. The result of F test above
shows the value of F arithmetic is 9,289 with a
significance value of 0.000. F table is obtained from
(V1 = k, V2 = n - k - 1) (Sujarweni, 2016). From F
distribution table for α = 0,05, F table V1 = 9 and
V2 = 71 is 2,015. From these results can be seen that
F arithmetic of 9,289 exceed F table of 2,015 so it
can be concluded that all independent variables in
this study affect the financial statement fraud
simultaneously.
4.3.2 Partial Regression Coefficient (t Test)
This test aims to show how far the influence of
independent variables individually explain the
dependent variable. The result of t test can be seen in
the table 4.3.
Table 4.3: t Test Results
Model
Standardized
Coefficients
t
Sig.
ACHAN
GE
,044
,472
,638
ROA
,202
1,982
,051
LEV
-,024
-,256
,799
OSHIP
-,021
-,248
,805
BDOUT
-,032
-,383
,703
RECEIV
-,600
-7,082
,000
AUDCH
ANGE
-,148
-1,712
,091
DCHAN
GE
-,118
-1,386
,170
CEOPIC
,009
,109
,914
The result of t test shows that there are three
independent variables that have positive value. The
variables are financial stability (ACHANGE),
financial target (ROA), and frequent number of
CEO’s picture (CEOPIC). It means that the three
independent variables have positive relation to
financial statement fraud. While the other six
independent variables are negative, which mean that
those variables have negative relation to financial
statement fraud. Those six variables are external
pressure (LEV), managerial ownership (OSHIP),
ineffective monitoring (BDOUT), nature of industry
(RECEIV), change in auditor (AUDCHANGE), and
change in directors (DCHANGE). This result also
shows that only one independent variable which has
significant influence on financial statement fraud
that is nature of industry (RECEIV). A variable can
be classified to have significant effect if the value of
Sig. < 0,05, the significance value of RECEIV is
0,000 while the other eight independent variables do
not have significant effect on financial statement
fraud due to the value of Sig. which exceeds 0,05.
4.4 Discussion
4.4.1 The Influence Of Financial Stability
On Financial Statement Fraud
Table 4.3 shows that financial stability has no
effect on financial statement fraud. Loebbecke et al.
(1989) and Bell et al. (1991) in Skousen et al (2008)
explain that when company's growth is below the
industry average, management can manipulate
financial statements to improve the company's
prospect. The company’s growth cannot be
separated from the state of economy in Indonesia. In
the period 2014 - 2016, Indonesian economy is
weak. Even the economic growth of Indonesia in
2015 is the lowest for 6 years (Wisanggeni, 2016).
Weak economy creates low demand for goods and
services so that company’s earnings are reduced.
Nevertheless, the government intensively increases
infrastructure development to improve Indonesia's
competitiveness which has been lagging behind
other developing countries in other regions
(Simorangkir, 2017).
Based on data from the Ministry of Public Works
and People's Housing cited in finance.detik.com,
several achievements that have been achieved in
infrastructure development consist of construction of
new roads, border roads, toll roads, bridges, dams,
and housing. The impact of these infrastructure
developments lead to rapid growth, for example in
one of infrastructure sector i.e. construction in recent
years (Petriella, 2017).
4.4.2 The Influence Of Financial Target On
Financial Statement Fraud
Based on Table 4.3, financial target has no effect
on financial statement fraud. The test result of ROA
in accordance with cognitive dissonance theory. In
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management accounting research, this theory
provides an explanation for how cognition or mental
representations mediate between budget goal
difficulty and performance (Jacob G, 2006). From
this theory can be concluded that someone who has
positive goal will not be disturbed by the act of fraud
because they will experience uncomfortable feelings
and it's not in accordance with their beliefs.
Companies that have individuals like this will reduce
the risk of fraud. Thus, higher corporate financial
target will increase employees' motivation to achieve
it with positive beliefs and behaviors.
4.4.3 The Influence Of External Pressure
On Financial Statement Fraud
The result shows that external pressure does not
affect the financial statement fraud. Richardson et al
(2004) explain that debt has high degree of
reliability, both short-term and long-term debt. Debt
accounts are company's liability against creditors or
suppliers that are recorded at nominal value. If the
company is going concern, then usually the
company must pay its debt in full. The only source
of subjectivity from debt account is discount
estimate for direct payments that suppliers may
offer. The amount of each discount is usually
verified by suppliers so the probability of error is
relatively small.
4.4.4 The Influence Of The Managerial
Ownership On Financial Statement
Fraud
The result indicates that managerial ownership
does not affect the financial statement fraud. Aprilia
(2017) explains that the less percentage of
managerial ownership in a company, the
management control will be smaller and this causes
the fraud higher. However, the higher percentage of
managerial ownership then fraud will be lower.
Company management will be more cautious about
financial statements if they have company shares as
it relates to their personal financial needs. Many
infrastructure companies in this study which their
shares are owned by management. In accordance
with the explanation, the more shares owned by
managerial then the company will be more careful
about the financial statements.
4.4.5 The Influence Of Ineffective
Monitoring On Financial Statement
Fraud
Based on table 4.3, ineffective monitoring does
not affect the financial statement fraud. Ineffective
monitoring is a condition where there is no effective
internal control system owned by company (Tessa &
Harto, 2016). Companies with small number of
independent board of commissioners will make
internal control ineffective and lead to increase
fraud. However, the result of this study measured
only by proportion rather than rules of function and
role of independent commissioners in minimizing
the risk of fraudulent financial statements as
described by Harahap et al (2017).
4.4.6 The Influence Of Nature Of Industry
On Financial Statement Fraud
The result shows that nature of industry affects
the financial statement fraud. Richardson et al
(2004) explain that receivable has low level of
reliability. It also involve subjective estimate of
uncollected receivable. In addition, receivable
account is the most commonly used accrual category
for manipulation. A low rate of change in receivable
indicates that the income received is also low and
the cash received will be small. This is what can
trigger the risk of financial statement fraud.
4.4.7 The Influence of Change in Auditor on
Finanial Statement Fraud
Based on table 4.3, The change in auditor does
not affect the financial statement fraud. Change in
auditor is not always related with fraud attempted to
be masked by the company. Article 22 in Peraturan
Pemerintah No. 20 of 2015 about the practice of
public accountant states that the limit of providing
audit services is 5 years. Auditor turnover can
happen because the limit period of public accounting
services provision has expired. In addition, auditor
turnover can be done as a result of companies that
are not satisfied with the performance of previous
independent auditor, for example from audited
results (Sihombing & Rahardjo, 2014).
4.4.8 The Influence of Change In Director
On Financial Statement Fraud
The result of this study shows that the change in
directors does not affect the financial statement
fraud. Change in directors is not always an
indication of the fraud occurring within the
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company. There are several factors that may
underlie the change in board of directors as specified
in the following rules or laws.
a. Article 105 paragraph 1 in Undang-Undang
Number 40 Year 2007 about Limited Liability
Company states that members of board of
directors may be dismissed at any time based on
the GMS decision by stating the reasons.
b. Article 8 paragraph 1 of Peraturan Otoritas Jasa
Keuangan No.33/POJK.04/2014 about Board of
Directors and Board of Commissioners of Issuers
or Public Companies states that members of
board of directors may resign from their
positions before their term of office expires.
c. Article 94 paragraph 3 in Undang-Undang
Number 40 Year 2007 regarding Limited
Liability Company states that members of board
of directors are appointed for a certain period and
can be reappointed. The term of board of
directors is contained in Article 3 paragraph 3 of
Peraturan Otoritas Jasa Keuangan
No.33/POJK.04/2014 which reads "1 (one)
tenure of board of directors no later than 5 (five)
years or until the closing of the Annual General
Meeting of Shareholders at the end of 1 (one)
tenure". This tenure makes the company through
GMS may appoint a new board of directors.
4.4.9 The Influence of Frequent Number of
CEO’s Picture on Financial Statement
Fraud
Table 4.3. shows that the frequent number of
CEO's picture does not affect the financial statement
fraud. Previously, Yusof et al (2015) explain that the
numbers of CEO's pictures show how he/she to be
known to the wider community and treat him/herself
as celebrity because of the arrogant nature. This
nature can be categorized as one of the
characteristics of narcissism. However, the number
of CEO's picture can be attributed to the positive
thing that is confidence. Confidence is built on the
success and achievement that has been achieved, the
life skills that have been mastered, the principles and
norms that are held firm, and the care shown to
others (Quamila, 2017).
5 CONCLUSIONS AND
SUGGESTIONS
5.1 Conclusion
Based on the background, theoretical basis,
hypothesis, and test results in this study, it can be
concluded that only nature of industry measured by
change in receivable ratio that affects financial
statement fraud. Other variables such as financial
stability, financial target, external pressure,
managerial ownership, ineffective monitoring,
change in auditor, change in directors, and frequent
number of CEO's picture have no influence on
financial statement fraud. However, these variables
simultaneously have significant influence on
financial statement fraud.
5.2 Suggestion
Next researchers are advised to use other
measuring tools of financial statement fraud such as
M-Score and Earning Management. Other variables
can also be used such as the quality of external
auditor, institutional ownership, and CEO politician.
Next researchers are also advised to expand the
population not only at infrastructure companies, but
other sectors like manufacturing and banking. While
investors and public are advised to perform an
analysis of the company's financial statements
before investing to avoid the loss, especially on
receivable because it has a big risk of fraud.
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