ANALISIS PENGARUH FRAUD HEXAGON DALAM MENDETEKSI POTENSI KECURANGAN LAPORAN KEUANGAN

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Abstract

The study aims to detect potential fraud in financial statement by using hexagon fraud theory which consists of pressure, opportunity, rationalization, capability, arrogance, and collusion. These elements are proxied using variables financial stability, external pressure, financial targets, nature of industry, change in auditors, change in directors, CEO’s picture, and government project and financial statements fraud as measured using the F-Score Model. Method purposive sampling used in this study, and a sample of 63 companies was obtained from a total of 92 mining sector companies listed on the Indonesia Stock Exchange during the 2016-2019 observation period. The analysis techniques were used is multiple linear regression with the SPPS program 25 version. The result of this study explain that the variables financial target has a positive effect and the change in director variable has a negative effect on fraudulent financial statements. Meanwhile the variables financial stability, external pressure, change in auditors, CEO’s picture and cooperation project with government have no significant effect on fraudulent financial statements.
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分析HEXAGON欺诈报表的影响
本研究的目的是利用六边形舞弊理论,即压力、机会、合理化、能力、傲慢和勾结,来发现财务报表中潜在的舞弊行为。这些因素使用变量来代理财务稳定性,外部压力,财务目标,行业性质,审计师的变化,董事的变化,CEO的形象,以及政府项目和财务报表欺诈,使用F-Score模型进行测量。方法本研究采用目的性抽样方法,在2016-2019年观察期内,从印尼证券交易所上市的92家矿业公司中抽取63家公司作为样本。分析技术采用多元线性回归与SPPS程序25版。本研究的结果解释了财务目标变量对财务报表舞弊具有正向影响,而董事变量的变动对财务报表舞弊具有负向影响。而财务稳定性、外部压力、审计师变动、CEO形象、政府合作项目等变量对财务报表舞弊的影响不显著。
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发文量
6
审稿时长
48 weeks
期刊最新文献
FINANCIAL FRAUD DETECTION AND MACHINE LEARNING ALGORITHM (UNSUPERVISED LEARNING): SYSTEMATIC LITERATURE REVIEW AUDIT COMMITTEE EFFECTIVENESS AS FRAUD PREVENTION MECHANISMS KETIDAKPASTIAN LINGKUNGAN DAN MANAJEMEN LABA DENGAN KEMAMPUAN MANAJERIAL SEBAGAI VARIABEL MODERASI MACHINE LEARNING FOR E-COMMERCE FRAUD DETECTION THE MODERATING ROLE OF ESG DISCLOSURE ON FIRM STRATEGY AND STOCK PRICE CRASH RISK
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