Jurnal Akuntansi P-ISSN 2303-0356 Vol. 10, No.3, Oktober 2020 (pp.231-244) E-ISSN 2303-0364 231 THE EFFECT OF FRAUD TRIANGLE IN DETECTING FINANCIAL STATEMENT FRAUD Zakharia Sabatian1)*, Francis M. Hutabarat2) Universitas Advent Indonesia1, 1,2) Zakharia3107@gmail.com1), fmhutabarat@unai.edu2) ABSTRACT Financial statements are a form of a report presented by a company that shows the financial performance of the company. In many cases of financial report fraud committed by Public Accounting Firm, they beautify the financial statements so that many investors are interested in the company. Therefore, this study aims to examine the influence of the Fraud Triangle factor in detecting fraudulent financial statements. The object of this study uses the financial statements of the Cigarettes and Cosmetics subsectors that are listed on the Indonesia Stock Exchange in the period 2016-2018. This study uses thirty sample data using purposive methods based on criteria. Data analysis using logistic linear regression analysis. The results showed that Rationalization had a significant effect on financial statement fraud. Meanwhile, Financial Stability, External Pressure, Personal Financial Need, Financial Targets, Ineffective Monitoring, Nature of Industry have no significant effect on financial statement fraud. Keywords: Fraud, Pressure, Opportunity, Rationalization, Financial Statement Fraud *Corresponding author Email: Zakharia3107@gmail.com DOI: https://doi.org/10.33369/j.akuntansi.10.3.231-244 INTRODUCTION A company aims to seek as much profit or profit as possible. Many of the foreign or local companies use improper methods to obtain these benefits, one of them cheating on financial statements. Financial statements are reports prepared by the company and can be a tool for management, even for investors to see the financial condition of the company. Financial statements have the objective of providing information about the entity's financial performance, financial position, and cash flows. Financial reports can show management's responsibility for the use of resources entrusted to it, and financial reports are very useful for users of financial statements in making economic decisions (Ikatan Akuntan Indonesia, 2015). From the definition stated above that the financial statements are also reported as a form of corporate accountability to the providers of resources, therefore the company is required to use these resources so that they can obtain the benefits that investors expect. Fraudulent financial statements are mistakes made intentionally in making financial reports, such as overstatement and others. Report fraud can be intentional or negligent in reporting financial statements, where the financial statements are presented not following the principle of generally acceptable accounting (Oktarigusta, 2017). Fraudulent financial statements can occur due to many factors, and usually, management wants the company to look good in financial terms. The act of manipulating financial statements is a form of fraud. Where financial reporting fraud is an attempt made deliberately by companies to deceive and mislead users of financial statements, especially investors and creditors, by presenting and manipulating the material value of financial statements (Sihombing & Rahardjo, 2014a). The phenomenon of fraud has occurred in many cases of fraudulent financial statements, so this is an urgent matter, since the phenomenon is about fraud cases many managers and decisions maker needs to know how to look at and determine whether it is a fraud case or not. mailto:Zakharia3107@gmail.com mailto:fmhutabarat@unai.edu mailto:Zakharia3107@gmail.com https://doi.org/10.33369/j.akuntansi.10.3.231-244 THE EFFECT OF FRAUD TRIANGLE IN DETECTING FINANCIAL STATEMENT FRAUD Zakharia Sabatian and Francis M. Hutabarat 232 Thus, the M score is one of the ratios that can be used by managers and decision-makers as a tool to make decisions whether there is fraud or not. Such as the case is taken from CNBC Indonesia about financial statements that have incorrect results of audits. This case was carried out by KAP Purwanto, Sungkoro, and Surja (Member of Ernst and Young Global Limited / EY). KAP Purwanto, Sungkoro, and Surja cheated financial statements at PT Hanson Internasional by overstatement revenue of Rp 613 billion. In addition to KAP Purwanto, Sungkoro, and Surja, there are also KAP Satrio, Bing, ENy & Partners (Deloitte Indonesia Partners). In October 2019 they were found to have given the wrong opinion to PT SNP Finance (Ayuningtyas, 2019). So that many parties are harmed, especially investors. The Indonesian Accounting Association has made PSAK (Statement of Financial Accounting Standards), this function so that financial reports can be reported properly and prevent fraud in financial statements. This study uses an independent variable, namely, the Fraud Triangle. The concept of the Fraud Triangle is divided into three, namely, Pressure, Opportunity, and Rationalization. This theory was made by Cressey (1953) and is still used by researchers today. Until now, fraud in financial reports still occurs frequently, so researchers try to use the Fraud Triangle concept with “Pressure” which can be categorized into four conditions, namely: First, Financial Stability using ACHANGE proxy. Because developing companies generally require a lot of assets and companies want to see their development quickly, they are prone to fraud in the asset division. Second, External Pressure uses LEV proxy. Because companies that have a high level of debt will have a low repayment capacity and they will also find it difficult to get additional through loans, therefore a high level of debt will allow management to commit fraud. Third, Personal Financial Need using OSHIP proxy. Because the executive has a financial or share the role in the company he leads, it will be very prone to financial statement fraud because all investors or shareholders want good financial reports. Forth, Financial Target uses ROA as a proxy. Because every company has an important goal of making a profit. In generating profits, every company needs to pay attention to principles so that the profits generated can be accounted for. Profitability is a measure to see the company's ability to generate profits. From various profitability ratios, ROA and ROE are often used to measure a company's ability to generate profits. And ROA is a ratio that describes, in general, the company's ability to generate profits based on total assets. “Opportunity” can be categorized into two conditions, namely: First, Nature of Industry using INVENTORY proxy. Because if the company has a larger amount of inventory than the previous year, it means that the company's finances have settled in the inventory and the company's financial turnover is disrupted. Thus, management will have the incentive to commit fraud so that the company's performance can still look good in the eyes of investors and other parties. Second, Ineffective Monitoring using BDOUT proxy. Ineffective is the condition of a company that does not have or lacks supervision of management so that management can be more flexible to commit fraud. Therefore, the importance of supervision from external parties, namely independent commissars. If there is less supervision from external parties, the chances of management committing fraud will be greater. “Rationalization” using TATA proxy, because the accrual concept is being able to record transactions even though there is no cashout or in, that's when management can commit fraud. As research conducted by Oktarigusta (2017), it is written that Rationalization is proxied by Total Accrual to Total Asset and Supervision Effectiveness which is proxied by the number of independent commissioners (BDOUT) has an effect on fraud in financial statements. However, research conducted by (Nugraheni & Triatmoko, 2016) states that effective monitoring, which is proxied by the number of independent commissioners, does not affect fraud in financial statements. So, from the previous research gap, this study aims to see the effect of Financial Stability, External Pressure, Personal Financial Need, Financial Targets, Effective Monitoring, Jurnal Akuntansi P-ISSN 2303-0356 Vol. 10, No.3, Oktober 2020 (pp.231-244) E-ISSN 2303-0364 233 Nature of Industry, Rationalization of Fraudulent Financial Statements in the cigarette, and cosmetics subsector companies for the period 2016-2018. And thus it is hoped that managers and decision-makers can see the relationship between the Fraud Triangle in this study with changes that can occur in fraudulent acts in companies that are proxied by the M-Score. THEORETICAL FRAMEWORK AND HYPOTHESIS Fraudulent Financial Statement A fraudulent Financial statement is often said to be a form of fraud that has the most detrimental impact (Reskino & Anshori, 2016). Financial Statement Fraud is an act that is intentionally carried out by a party or makes a mistake in the presentation of the financial report and has a material error value (Annisya et al., 2016). According to (Koroy, 2008), if an act is deliberate and the action is not detected by the auditing process, this can have a very detrimental and flawed effect on the financial reporting process, the existence of fraud has serious consequences and brings many losses to the company. Beneish M-Score Model The Beneish M-Score Model is a model developed using logistic regression and this model uses eight financial ratios. The eight financial ratios contained in the model are determined and tested using the principal component analysis and this model is useful for predicting fraudulent financial statements - earnings management (Beneish, 1999). Sales general administrative index (SGAI), days sales receivable index (DSRI), leverage index (LVGI), gross margin index (GMI), depreciation index (DEPI), sales growth index (SGI), total accruals to total assets (TATA), and the asset quality index (AQI) are the eight ratios in the M- Score Model. The eight ratios are then entered into the formulation and if the Beneish M-Score value is greater than -2.22 it has the predicate of containing fraud (Tarjo & Herawati, 2015). Beneish (1999) also states that all variables have a significant positive relationship with fraudulent financial statements. Triangle Fraud Fraud is an action taken to seek profit unnaturally. Fraud is also a serious problem that occurs in many countries, by all means, do it. Especially now that cases of Fraud are becoming more prevalent among companies going public, therefore the Fraud case must be a concern for many people, especially for academics (Irianto & Noviati, 2018). Cressey said that the Fraud triangle consisting of Pressure, Opportunity, and Rationalization can explain why people commit fraud. Pressure can be likened to a source of heat that makes fire or a fraud act, and there is also research that says that Opportunity is a fuel that keeps a fire burning or a fraud action that occurs. While rationalization is likened to oxygen or an act of violation (Lister, 2007). In the SAS statement, No.99 Pressure can be categorized into four conditions, namely: Financial Stability, External Pressure, Personal Financial Needs, and Financial Targets. Opportunity can be categorized into two conditions, namely: Nature of Industry and Effective Monitoring. Financial Stability and Fraudulent Financial Fraud Financial Stability is a state of company financial stability. When the company's finances are unstable, management is required to keep the company's finances stable. In No. SAS 99, when the financial stability or profitability is poor or below average due to the economic situation, industry, or the situation of the operating entity, managers will experience pressure to commit financial statement fraud (Skousen & Twedt, 2009). This is what makes management commit fraud on the financial statements, especially in terms of assets, usually, a growing company requires more assets to develop its business. The growth of changes in THE EFFECT OF FRAUD TRIANGLE IN DETECTING FINANCIAL STATEMENT FRAUD Zakharia Sabatian and Francis M. Hutabarat 234 company assets is often used as a form of fraudulent financial reporting by management (Aprilia et al., 2017), therefore assets can be categorized as fraudulent. Financial Stability can be measured or proxied using ‘ACHANGE’, which is the percentage change in assets during the last two years before the occurrence of fraud (Maghfiroh et al., 2015). The results of research conducted by (Aprilia et al., 2017) and (Listyaningrum et al., 2017), said that Financial Stability has a positive effect on Financial Statement Fraud. Based on previous theory and research, Financial Stability can be used to detect fraudulent financial statements. H1: Financial Stability has a positive effect on financial statement fraud. External Pressure and Fraudulent Financial Fraud External Pressure is the pressure given by a third party to meet the expectations of a third party (Daljono, 2013). Companies that are under excessive pressure need additional sources of funds through debt. When management experiences a debt covenant violation, the manager will rely more on discretionary accruals, which then levels the debt with an increase in discretionary accruals. Furthermore, managers will feel that this pressure occurs because of the additional need to obtain more debt to remain competitive (Oktarigusta, 2017). The company's need for external financing will be related to cash from operating activities (Skousen & Twedt, 2009). Therefore, external pressure can be proxied using the leverage ratio. The results of research conducted by (Nugraheni & Triatmoko, 2016) and (Utama et al., 2018) stated that External Pressure has a positive effect on Fraudulent Financial Statements. Based on previous theory and research, External Pressure can be used to detect Fraudulent Financial Statements. H2: External Pressure has a positive effect on Financial Statement Fraud. Personal Financial Need and Fraudulent Financial Fraud Personal Financial Need in this research refers to the financial needs of shareholders owned by company executives, namely, the board of commissioners, the board of directors, and others. When company executives have a strong financial role in the company, the personal financial needs of the company executives will also influence the company's financial performance (Molida, 2011). Shares owned by executives can influence management policies when disclosing the company's financial performance (Molida, 2011). Therefore, the Personal Financial Need can be proxied using the Managerial Ownership (OSHIP) ratio. The results of research conducted by (Oktafiana et al., 2019) and (T. P. Sari & Lestari, 2020) state that Personal Financial Need has a positive effect on Financial Statement Fraud. Based on previous theory and research, the Personal Financial Need can be used to detect Financial Statement Fraud. H3: Personal Financial Need has a positive effect on Fraudulent Financial Statements Financial Targets and Fraudulent Financial Fraud Financial Target is excessive pressure from management to achieve the company's financial targets (Sholihah, 2014). Company managers have a responsibility to perform the best and aim to achieve the financial targets that have been planned by the company (Sihombing & Rahardjo, 2014b). Companies generally have financial objectives: faster profit growth, wider profitability, wider revenue growth, higher share, higher stock returns, rising share prices, more stable profits in recession periods, recognition as a blue-chip company. Because of the many financial goals that must be met, management will have excessive pressure to achieve the company's financial targets or targets (Robbins & Mary, 2004). In this study, ROA (Return on Assets) is an indicator of Financial Targets because this profitability ratio can measure the company's ability to achieve targeted profits with existing assets. The results of research conducted by (Putri et al., 2017) and (Agusputri & Sofie, 2019) state that Financial Targets have a positive effect on Financial Statement Fraud. Based on Jurnal Akuntansi P-ISSN 2303-0356 Vol. 10, No.3, Oktober 2020 (pp.231-244) E-ISSN 2303-0364 235 previous theory and research, the Financial Target can be used to examine Financial Statement Fraud. H4: Financial Targets have a positive effect on Fraudulent Financial Statements. Nature of Industry and Fraudulent Financial Fraud The nature of Industry is the benchmark for a company in an industry. In a place where companies operate, the economic environment and industrial regulations often become one of the loopholes for companies to commit fraudulent financial statements (Aulia, 2018). In the financial statements, the outdated inventory account, the balance is determined by the company, and the company as an internal party has more information so that this situation can be exploited by the company to become a loophole in committing fraud (Apriyani & Ritonga, 2019). The risk of financial statement fraud can be seen from the inventory account (Skousen et al in Mawarni, 2016). In this study, INVENTORY is an indicator of the Nature of Industry because inventory accounts are usually assessed subjectively to estimate uncollectible accounts. The results of research conducted by (Patimah, 2019) and (Yulia, 2018) state that the Nature of Industry has a positive effect on Financial Statement Fraud. Based on previous theory and research, the Nature of Industry can be used to detect Fraudulent Financial Statements. H5: Nature of Industry has a positive effect on Financial Statement Fraud. Ineffective Monitoring and Fraudulent Financial Fraud Ineffective Monitoring is the condition of a company that does not have an effective supervisor who can monitor the company's performance. Poor supervision will provide an opportunity to conduct Financial Statement Fraud (Pamungkas, 2018). Ineffective Monitoring often occurs because of the dominance of management by a small group of parties. So that it opens up opportunities for managers to cheat financial statements (Apriyani & Ritonga, 2019). The way to overcome this problem is of course by providing supervision to the management. Companies can give trust to external parties as supervisors because external supervisors have no relationship with management or investors. So it can be said that external parties are more independent (Apriyani & Ritonga, 2019). In this study, the Proportion of Independent Commissioners becomes an indicator of effective monitoring because, the higher the proportion of independent commissioners, the less will they commit fraud. The results of research conducted by (Aprilia et al., 2017) and (Putri et al., 2017) state that ineffective monitoring has a positive effect on Fraudulent Financial Statements. Based on previous theory and research, effective monitoring can be used to detect Fraudulent Financial Statements. H6: Ineffective Monitoring has a positive effect on Fraudulent Financial Statements Rationalization and Fraudulent Financial Fraud One of the important components of fraud is rationalization. Rationalization allows fraudsters to justify mistakes that have been made (S. T. Sari et al., 2016). Assessment and subjective decision making will be seen in the company's accrual value. A large amount of revenue in the total accrual value can cause the company to indicate financial reporting fraud, even when the total accrual value is greater than cash, it does not rule out the possibility of large revenue manipulation (Agusputri & Sofie, 2019). Rationalization, which is proxied by the Ratio of Total Accrual to Total Assets (TATA), can justify actions in fraudulent financial statement activities. Fraudulent financial statements are often due to management insisting on fraudulent accounting practices that they have committed which is reflected in the large number of accrual products that appear in financial reports (Aprillia et al., 2015). The results of research conducted by (Iqbal & Murtanto, 2016) and Oktarigusta (2017) state that rationalization has a positive effect on Financial Statement Fraud. Based on previous theory and research, Rationalization can be used to detect Fraudulent Financial Statements. THE EFFECT OF FRAUD TRIANGLE IN DETECTING FINANCIAL STATEMENT FRAUD Zakharia Sabatian and Francis M. Hutabarat 236 H7: Rationalization has a positive effect on Financial Statement Fraud. METHODS This study uses a population of 7 cigarette subsector companies and 5 cosmetics subsector companies listed on the Indonesia Stock Exchange for the period 2016-2018. This study uses a purposive sampling technique and has several criteria, including: 1. Cigarette and Cosmetics subsector companies listed on the IDX. 2. The company has been listed on the IDX starting one year before the research period (2015) and during the research period (2016-2018). 3. Companies that have an audited Annual Report from 2016-2018. 4. The company did not experience delisting during the observation period. The samples obtained by researchers were 18 annual reports of cigarette companies and 12 annual reports of cosmetic companies. Data collection uses documentation techniques by downloading annual reports obtained from the website www.idx.co.id. The data collected were obtained using IBM SPSS Statistic 25 software and using logistic regression analysis techniques. Here is a model of Logistic regression that is used to test hypotheses: Log 𝑝 1−𝑝 = α+β1ACHANGE+β2LEV+β3OSHIP+β4ROA+β5INVENTORY+β6BDOUT+β7TATA+e Explanation: Log 𝑝 1−𝑝 = Fraud Activity α = Regression Constant β1 ACHANGE = Assets Change Constant β2 LEV = Leverage Constant β3 OSHIP = Managerial Ownership Constant β4 ROA = Return on Assets Constant β5 INVENTORY = Total Inventory Ratio Constant β6 BDOUT = Proportion of Independent Commissioners Constant β7 TATA = Total Accrual to Total Assets Constant This study makes the Fraud Financial Statement the dependent variable and is proxied by the Beneish M-Score Formula. Beneish M-Score has several ratios to calculate it, namely, Day Sales Index in Accounts Receivable, Gross Margin Index, Asset Quality Index, Sales Growth Index, Depreciation Index, Sales, and General Administration Expense Index, Leverage Index, Total Accruals. Table 1. Beneish M-Score Ratio Formula Days Sales in Receivables Index 𝐷𝑆𝑅𝐼 = (𝑁𝑒𝑡 𝑅𝑒𝑐𝑒𝑖𝑣𝑎𝑏𝑙𝑒𝑠 𝑡/𝑆𝑎𝑙𝑒𝑠 𝑡) (𝑁𝑒𝑡 𝑅𝑒𝑐𝑒𝑖𝑣𝑎𝑏𝑙𝑒𝑠 𝑡 − 1/𝑆𝑎𝑙𝑒𝑠𝑡 − 1) Gross Margin Index 𝐺𝑀𝐼 = [(𝑆𝑎𝑙𝑒𝑠 𝑡 − 1 − 𝐶𝑜𝑔𝑠 𝑡 − 1)/𝑆𝑎𝑙𝑒𝑠 𝑡 − 1] [(𝑆𝑎𝑙𝑒𝑠 𝑡 − 𝐶𝑜𝑔𝑠 𝑡)/𝑆𝑎𝑙𝑒𝑠 𝑡 − 1] Assets Quality Index 𝐴𝑄𝐼 = (𝑇𝐴 𝑡 − (𝐶𝐴 𝑡 + 𝑃𝑃𝐸 𝑡)/𝑇𝐴 𝑡) (𝑇𝐴 𝑡 − 1 − (𝐶𝐴 𝑡 − 1 + 𝑃𝑃𝐸 𝑡 − 1)/𝑇𝐴 𝑡 − 1) Sales Growth Index 𝑆𝐺𝐼 = 𝑆𝑎𝑙𝑒𝑠 𝑡 𝑆𝑎𝑙𝑒𝑠 𝑡 − 1 Depreciation Index 𝐷𝐸𝑃𝐼 = [(𝐷𝑒𝑝𝑟𝑒 𝑡 − 1/(𝑃𝑃𝐸 𝑡 − 1 + 𝐷𝑒𝑝𝑟𝑒 𝑡 − 1)] [(𝐷𝑒𝑝𝑟𝑒 𝑡/(𝑃𝑃𝐸 𝑡 + 𝐷𝑒𝑝𝑟𝑒 𝑡)] Jurnal Akuntansi P-ISSN 2303-0356 Vol. 10, No.3, Oktober 2020 (pp.231-244) E-ISSN 2303-0364 237 After the eight ratios have been obtained, everything will be calculated using the following formula: M-Score = -4.84 + 0.92DSRI + 0.528GMI + 0.404AQI + 0.892SGI + 0.115DEPI - 0.172SGAI + 4.679DATA - 0.327LVGI. If the result of M-Score> -2.22, the company is categorized as cheating financial statements, and vice versa if the results of M- Score <-2.22, the company is not categorized as cheating financial statements (Mardianto & Tiono, 2019). The independent variable in this study uses the Fraud Triangle, where the Fraud Triangle is divided into three parts, namely: Pressure, Opportunity, and Rationalization (Andriani, 2019). ‘Pressure’ has four categories, namely: Financial Stability which is proxied by Assets Change (ACHANGE), External Pressure which is proxied by Leverage (LEV), Personal Financial Need which is proxied by Managerial Ownership (OSHIP), and Financial Target which is proxied by using Return on Assets (ROA). ‘Opportunity’, has two categories, namely: Nature of Industry which is proxied by the Ratio of Total Inventory (INVENTORY), and Ineffective Monitoring which is proxied by the Proportion of the Number of Independent Commissarine Boards (BDOUT). ‘Rationalization’, which is proxied by the Total Accrual Ratio (TATA). Table 2. Fraud Triangle Ratio Rumus Assets Change (ACHANGE) 𝐴𝑐ℎ𝑎𝑛𝑔𝑒 = 𝑇𝐴 𝑡 − 𝑇𝐴 (𝑡 − 1) 𝑇𝐴 𝑡 Leverage (LEV) 𝐿𝐸𝑉 = 𝑇𝑜𝑡𝑎𝑙 𝐷𝑒𝑏𝑡 𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠 Managerial Ownership (OSHIP) 𝑂𝑆𝐻𝐼𝑃 = 𝑇𝑜𝑡𝑎𝑙 𝐼𝑛𝑠𝑖𝑑𝑒𝑟 𝑆ℎ𝑎𝑟𝑒𝑠 𝑇𝑜𝑡𝑎𝑙 𝑂𝑟𝑑𝑖 𝑆ℎ𝑎𝑟𝑒𝑠 𝑂𝑢𝑡𝑠𝑎𝑛𝑑𝑖𝑛𝑔 Return on Assets (ROA) 𝑅𝑂𝐴 = Net Income 𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠 Total Inventory Ratio (INVENTORY) 𝐼𝑁𝑉𝐸𝑁𝑇𝑂𝑅𝑌 = 𝐼𝑛𝑣𝑒𝑛 𝑡 𝑆𝑎𝑙𝑒𝑠 𝑡 + 𝐼𝑛𝑣𝑒𝑛 𝑡 − 1 𝑆𝑎𝑙𝑒𝑠 𝑡 − 1 The proportion of Independent Commissioners (BDOUT) 𝐵𝐷𝑂𝑈𝑇 = 𝐼𝑛𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑡 𝐶𝑜𝑚𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑒𝑟𝑠 𝐵𝑜𝑎𝑟𝑑 𝑜𝑓 𝐶𝑜𝑚𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑒𝑟𝑠 Total Accrual to Total Assets (TATA) 𝑇𝐴𝑇𝐴 = (𝑁𝑒𝑡 𝐼𝑛𝑐𝑜𝑚𝑒 − 𝐶𝐹𝑂) 𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠 RESULT This study has thirty samples and below are the results of the descriptive table. The table below shows descriptive statistics that contain the Min, Max, Mean, and Standard Dev. Table 3. Statistics Descriptive n Min Max Mean Stand. Dev ACHANGE 30 -.20 .15 .0371 .06670 LEV 30 .18 .76 .4124 .18438 OSHIP 30 .00 .38 .0469 .10947 ROA 30 -.18 .47 .0918 .14834 INVENTORY 30 -.55 .10 -.0503 .17085 BDOUT 30 .20 1.00 .4472 .19981 Sales and General Adm Expenses Index 𝑆𝐺𝐴𝐼 = (𝑆𝐺&𝐴 𝐸𝑥𝑝 𝑡/ 𝑆𝑎𝑙𝑒𝑠 𝑡) (𝑆𝐺&𝐴 𝐸𝑥𝑝 𝑡 − 1/ 𝑆𝑎𝑙𝑒𝑠 𝑡 − 1) Leverage Index 𝐿𝑉𝐺𝐼 = [(𝐶𝑢𝑟𝑟𝑒𝑛𝑡 𝐿𝑖𝑎𝑏 𝑡 + 𝐿𝑜𝑛𝑔𝑇𝑒𝑟𝑚𝐷𝑒𝑏 𝑡)/𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡 𝑡] [(𝐶𝑢𝑟𝑟𝑒𝑛𝑡 𝐿𝑖𝑎𝑏 𝑡 − 1 + 𝐿𝑜𝑛𝑔𝑇𝑒𝑟𝑚𝐷𝑒𝑏 𝑡 − 1)/𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡 𝑡 − 1] Total Accrual to Total Assets 𝑇𝐴𝑇𝐴 = (𝑁𝑒𝑡 𝐼𝑛𝑐𝑜𝑚𝑒 − 𝐶𝐹𝑂) 𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠 THE EFFECT OF FRAUD TRIANGLE IN DETECTING FINANCIAL STATEMENT FRAUD Zakharia Sabatian and Francis M. Hutabarat 238 n Min Max Mean Stand. Dev TATA 30 -.19 .12 -.0230 .06446 The table above shows the characteristics of the variable in the study. Fraud Triangle is the independent variable with three components comprise of Pressure, Opportunity, and Rationalization. Pressure as the first Fraud Triangle has its component, they are ACHANGE, LEV, OSHIP, and ROA. In terms of ACHANGE, it has a mean value of 0.0371 with a maximum value of .15. In terms of Leverage, it has a mean value of 0.4124. In terms of Managerial Ownership, it has a mean result of 0.0469 or 4.69% with a maximum value of 38% ownership. In terms of ROA, the result shows a mean of 9.18% means the maximum value of 47%. Opportunity as the second Fraud Triangle has components such as Inventory and BDOUT. In terms of Inventory, the mean value is -0.0503 with a maximum value of .10. in terms of BDOUT, it has a mean value of 44.72. Rationalization as the third Fraud Triangle has one component in the study which is TATA. In terms of TATA, the mean value is -0.0230 with a maximum value of 0.12 and a minimum value of -0.19. Therefore, it is safe to say that companies in the consumption subsector consist of cigarettes and cosmetic companies have a good ability to gain profit in terms of ROA, adequate terms of leverage, Good Proportion of Ineffective Monitoring in terms of a board director. Rationalization has a subjective assessment of the company, subjective judgment and decision making will be reflected in the negative accrual value of the company Table 4. Table Frequency Fraud Frequency % Valid % Cumulative % Valid .00 23 76.7 76.7 76.7 1.00 7 23.3 23.3 100.0 Total 30 100.0 100.0 Based on the table above, the researcher used 30 samples of financial statements and used code 1, which means committing fraud, and code 0, which means not committing fraud. This table shows that there are 7 financial reports or 23.3% of financial reports that committed fraud and 23 financial statements or 76.7. % Financial reports that did not commit as many frauds. Table 5. Lemeshow and Hosmer Test Step Ch-square Df Sgnfi 1 4.860 8 .772 Table 5 shows the results of the model feasibility test, the Hosmer and Lemeshow Test value of 4,860, and a significant value of 0.772. The significance value is greater than 5%, meaning that the model in this study is acceptable. Table 6. -2 Lg Likelihood Constant -2 Log likelihood Beginning -2 Log-likelihood 32.679 Ending -2 Log-Likelihood 13.716 The overall assessment of the model can be assessed by comparing the results between the beginning -2 Lg likelihood and the ending -2 Lg likelihood value. The Log-Likelihood value at the beginning was 32.679 and the Log-Likelihood value at the end decreased by 18.963 to 13.716. A decrease in log-likelihood indicates that the hypothesized model matches the data. The results of the overall model research can be seen in Table 6. Table 7. Omnibus Test Ch-square df Sg. Step Step 18.881 7 .009 Jurnal Akuntansi P-ISSN 2303-0356 Vol. 10, No.3, Oktober 2020 (pp.231-244) E-ISSN 2303-0364 239 Ch-square df Sg. 1 Block 18.881 7 .009 Model 18.881 7 .009 The table shows that the value of the omnibus test was obtained by chi-square (a decrease in the value of -2 log-likelihood) of 18,881 with a significance of 0.009. The significance value obtained is smaller than the α level of 0.05, indicating the significant influence of the seven predictors in this study that together can explain the possibility of financial statement fraud. Table 8. Model Summary Step -2 Lg likelihood Snel R Sqre & Cox Naglkerke R Sqre 1 13.716a .467 .705 Nagelkerke R Square value shows the relationship of independent variables to the dependent variable. It can be seen from Table 8 that shows the Nagelkerke R Square value of 0.705 which means that variations of Pressure, Opportunity, and Rationalization can interpret Fraud by 70.5%, while the other 29.5% is explained by other variables not included in the regression model. Table 9. Fraud Prediction Classification Tablea Observed Predicted FRAUD Percentage Correct .00 1.00 Step 1 FRAUD .00 21 2 91.3 1.00 3 4 57.1 Overall Percentage 83.3 The number of samples that did not commit fraud in table 4 there are 23 samples, but after being tested again in table 9, it is found that 21 samples did not commit fraud and 2 samples committed fraud again. And in table 4 7 samples committed fraud, but after being tested again, it turns out that there are 4 samples and 3 samples who did not commit fraud. Based on this explanation, the overall value becomes (21 + 4) / 30x100% = 83.3%, where this result has an interpretation that the accuracy of this model is very good because it is close to 100%. Table 10. Regression Logistic Analysis Variables in the Equation B S.E. Wald df Sig. Exp(B) Step 1a ACHAN GE -20.005 18.159 1.214 1 .271 .000 LEV -5.674 6.752 .706 1 .401 .003 OSHIP -48.899 37.272 1.721 1 .190 .000 ROA -1.812 6.458 .079 1 .779 .163 INVEN TORY -41.197 26.817 2.360 1 .124 .000 BDOUT -6.750 7.748 .759 1 .384 .001 TATA 66.012 34.711 3.617 1 .057 46616292474 40085000000 0000000.000 Constant 5.311 5.822 .832 1 .362 202.575 The results of the calculation of logistic regression analysis according to the table above, obtained the following equation: Log = 5.311-20.005ACHANGE-5.674LEV-48.899OSHIP-1.812ROA-41.197 INVENTORY -6.750BDOUT+66.012TATA THE EFFECT OF FRAUD TRIANGLE IN DETECTING FINANCIAL STATEMENT FRAUD Zakharia Sabatian and Francis M. Hutabarat 240 Interpretation: 1. The constant value of 5.311 shows that if ACHANGE, LEV, OSHIP, ROA, INVENTORY, BDOUT, and TATA are assumed to be zero, then financial statement fraud (FRAUD) will increase. 2. From the results of the hypothesis test shows the variable regression coefficient of ACHANGE (-20.005), LEV (-5.674), OSHIP (-48.899), ROA (-1.812), INVENTORY (- 41.197), BDOUT (-6.750) are negative. This shows that the increase in ACHANGE, LEV, OSHIP, ROA, INVENTORY, BDOUT will decrease the financial statement fraud. 3. From the results of the hypothesis test shows the variable regression coefficient of TATA (66.012) is positive. This shows that the increase in TATA will increase the financial statement fraud. DISCUSSION The first hypothesis states that changes in total assets have a significant positive effect on fraud. Variable ACHANGE which is a component of the first Fraud Triangle which is Pressure shows a regression coefficient of -20.005 with a variable probability value of 0.271 which is greater than the significance level of 0.05 (5%). The test results showed that H1 was rejected, and showed that ACHANGE did not have a significant relationship with fraud in the financial statements of the cigarette and cosmetics sector companies on the IDX. This significant value indicates that if the ACHANGE is high, it is not always followed by the occurrence of fraudulent activities. This research differed from previous research by (Iqbal & Murtanto, 2016) but the same as previous research by (Oktarigusta, 2017). The second hypothesis states that leverage has a significant positive effect on fraud. The LEV variable which is the first component of the Fraud Triangle, namely Pressure, shows a regression coefficient of -5,674 with a variable probability value of .401 which is greater than the significance level of 0.05 (5%). The test results showed that H2 was rejected, and showed that LEV did not have a significant relationship with fraud in the financial statements of cigarette and cosmetics sector companies on the IDX. This significant value indicates that if the LEV is high, it is not always followed by the occurrence of fraudulent activities. This research differed from previous research by Iqbal & Murtanto (2016) but the same with previous research by Oktarigusta (2017). The third hypothesis states that Managerial Ownership has a significant positive effect on fraud. The OSHIP variable which is a component of the first Fraud Triangle namely Pressure shows a regression coefficient of -48.899 with a variable probability value of .190 which is greater than the significance level of 0.05 (5%). The test results showed that H3 was rejected, and showed that OSHIP did not have a significant relationship with fraud in the financial statements of the cigarette and cosmetics sector companies on the IDX. This significant value indicates that if the OSHIP is high, it is not always followed by the occurrence of fraudulent activities. This Research differed from previous research by Iqbal & Murtanto (2016) but the same with previous research by Aprilia et al (2017). The fourth hypothesis states that Return on Assets has a significant positive effect on fraud. The ROA variable which is a component of the first Fraud Triangle namely Pressure shows a regression coefficient of -1.812 with a variable probability value of .779 which is greater than the significance level of 0.05 (5%). The test results showed that H4 was rejected, and showed that ROA did not have a significant relationship with fraud in the financial statements of the cigarette and cosmetics sector companies on the IDX. This significant value indicates that if the ROA is high, it is not always followed by the occurrence of fraudulent activities. This research differed from previous research by Iqbal & Murtanto (2016) but the same with previous research by Annisya et al (2016). Jurnal Akuntansi P-ISSN 2303-0356 Vol. 10, No.3, Oktober 2020 (pp.231-244) E-ISSN 2303-0364 241 The fifth hypothesis states that the Total Inventory Ratio has a significant positive effect on fraud. The INVENTORY variable which is a component of the second Fraud Triangle namely Opportunity shows a regression coefficient of -41.197 with a variable probability value of .124 which is greater than the significance level of 0.05 (5%). The test results showed that H5 was rejected, and showed that INVENTORY did not have a significant relationship with fraud in the financial statements of the cigarette and cosmetics sector companies on the IDX. This significant value indicates that if the INVENTORY is high, it is not always followed by the occurrence of fraudulent activities. This research differed from previous research by Iqbal & Murtanto (2016) but the same with previous research by Annisya et al (2016). The sixth hypothesis states that Supervision Effectiveness has a significant positive effect on fraud. The BDOUT variable which is a component of the second Fraud Triangle namely Opportunity shows a regression coefficient of -6.750 with a variable probability value of .384 which is greater than the significance level of 0.05 (5%). The test results showed that H6 was rejected, and showed that BDOUT did not have a significant relationship with fraud in the financial statements of the cigarette and cosmetics sector companies on the IDX. This significant value indicates that if the BDOUT is high, it is not always followed by the occurrence of fraudulent activities. This research differed from previous research by Iqbal & Murtanto (2016) and Oktarigusta (2017) but the same with previous research by Aprilia et al (2017). The seventh hypothesis states that Rationalization has a significant positive effect on fraud. The TATA variable which is a component of the third Fraud Triangle namely Rationalization shows a regression coefficient of 66.012 with a variable probability value of .057 which is smaller than the significance level of 0.01 (10%). The test results showed that H7 was accepted, and showed that TATA has a significant relationship with fraud in the financial statements of the cigarette and cosmetics sector companies on the IDX. This significant value indicates that if TATA is high, it will be followed by the occurrence of fraudulent activities. This research came from previous research by Iqbal & Murtanto (2016) and Oktarigusta (2017). CONCLUSIONS AND SUGGESTION Based on the result of this research the conclusion that is drawn from the study is that in terms of Fraud Triangle Pressure, the proxy variable of pressure cannot explain the variability of fraud, since Financial Stability is not significantly affecting fraud, External Pressure is not significantly affecting fraud, Personal Financial Need is not significantly affecting fraud, and Financial Target is not significantly affecting fraud. In terms of Fraud Triangle Opportunity, the proxy variable of Opportunity cannot explain the variability of fraud, since the Nature of Industry is not significantly affecting fraud, and Ineffective Monitoring is not significantly affecting fraud. So, from this research, it can be seen that the opportunity and pressure that are proxied by using Financial Stability, External Pressure, and Personal Financial Needs, Financial Target, Nature of Industry, and Ineffective Monitoring do not influence financial statement fraud. It can also be said that if pressure and opportunity have a high value, the company does not necessarily commit fraud. In terms of Fraud Triangle Rationalization, the proxy variable of Rationalization can explain the variability of fraud, since Rationalization is significantly affecting fraud. Total Assets to Total Accrual is directly proportional to fraud because it has a positive significant value. It can be concluded that the higher the Total Assets to Total Accrual the higher the probability of the company committing fraud. Further research is recommended adding a few more variables that are proxy using the number of commissioners, the ratio of sales to receivables, changes in directors. Further THE EFFECT OF FRAUD TRIANGLE IN DETECTING FINANCIAL STATEMENT FRAUD Zakharia Sabatian and Francis M. Hutabarat 242 research is suggested to add samples of other sector companies such as manufacturing or trade. Extend the period of the company under study. There are two implications in this research, the first is the theoretical implication, that is, this research is expected to increase knowledge about the influence of the Fraud Triangle indicator on the Fraud Financial Statement. The practical implications are: for investors, considering investors who will invest, whether the company can be categorized as fraud or not. For Management, building a good and strong internal control system to close or minimize fraud. For decision-makers and managers, they can see that the relationship between indicators of rationalization or high total assets to total accrual will have the potential for fraud in the financial statements, therefore the decision-maker can make better decisions. REFERENCES Agusputri, H., & Sofie, S. (2019). Faktor - Faktor Yang Berpengaruh Terhadap Fraudulent Financial Reporting Dengan Menggunakan Analisis Fraud Pentagon. 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