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{"references": ["Aprilia, R. (2017). Pengaruh Financial Stability, Personal Financial Need, Ineffective Monitoring, Change In Auditor Dan Change In Director terhadap Financial Statement Fraud dalam Perspektif Fraud Diamond. JOM Fekon, 4(1), 1472\u2013 1486", "Apriyani, N. K., & Ritonga, F. (2019). Nature of Industry dan Ineffective Monitoring sebagai Determinan Terjadinya Fraud dalam Penyajian Laporan Keuangan. JSMA (Jurnal Sains Manajemen Dan Akuntansi), XI(2), 1\u2013 28", "] Bawekes, H. F., Simanjuntak, A. M., & Christina Daat, S. (2018). Pengujian Teori Fraud Pentagon Terhadap Fraudulent Financial Reporting (Studi Empiris pada Perusahaan yang Terdaftar di Bursa Efek Indonesia Tahun 2011-2015). Jurnal Akuntansi & Keuangan Daerah, 13(1), 114\u2013134.", "Desviana, D., Basri, Y. M., & Nasrizal, N. (2020). Analisis Kecurangan pada Pengelolaan Dana Desa dalam Perspektif Fraud Hexagon. Studi Akuntansi Dan Keuangan Indonesia, 3(1), 50\u201373. https://doi.org/10.21632/saki.3.1.50-73", "Diyanty, V. (2022). HEXAGON FRAUD IN FRAUDULENT FINANCIAL STATEMENTS : 19(1). https://doi.org/10.21002/jaki.2022.03", "Fransesco, T., Patty, Q., & Ardini, L. (2021). RISIKO KECURANGAN LAPORAN KEUANGAN PEMERINTAH PADA MASA PANDEMI COVID-19. 10(2).", "Ghozali, I. (2013). Aplikasi Analisis Multivariate dengan Program IBM SPSS 21 Update PLS Regresi", "Hantono, . . (2018). Deteksi Financial Statement Fraud Melalui Model Beneish Pada Perusahaan Bumb. JMBI UNSRAT (Jurnal Ilmiah Manajemen Bisnis Dan Inovasi Universitas Sam Ratulangi)., 5(3), 135\u2013150. https://doi.org/10.35794/jmbi.v5i3.21705"]}
According to Statement of Financial Accounting (SFAC) No. 1, users of financial statements have a considerable worry regarding profit information in the company's financial statements when evaluating performance and the company's earning potential in the future. The purpose of this study was to examine the effect of external pressure, nature of industry, rationalization, capability, arrogance, collusion, and covid-19 on fraudulent financial statements. The research sample is a manufacturing company in the goods and consumption sector which is listed on the Indonesia Stock Exchange for the 2018-2021 period. Sampling in this study uses a purposive sampling method. The number of samples is 46 companies per year, with the amount of data studied being 147. This study's analysis method makes use of multiple linear regression analysis. M-Score for Beneish, this model was created using logit regression to predict false financial statements (fraud). The origin the following variables can be identified based on the outcomes of the data processing shown above: Variable H2 is approved since the nature of the industry has a considerable favorable impact on false financial statements. This occurs because businesses with a lot of receivables are vulnerable to manipulation
Fraud Hexagon, Financial Statement, Fraudulent Financial Statement, Covid-19, Fraud,
Fraud Hexagon, Financial Statement, Fraudulent Financial Statement, Covid-19, Fraud,
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