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All issues Volume 388 (2023) E3S Web of Conf., 388 (2023) 01015 References
Open Access
Issue
E3S Web of Conf.
Volume 388, 2023
The 4th International Conference of Biospheric Harmony Advanced Research (ICOBAR 2022)
Article Number 01015
Number of page(s) 7
Section Sustainable Infrastucture, Industry, Architecture, and Food Technology
DOI https://doi.org/10.1051/e3sconf/202338801015
Published online 17 May 2023
  1. V. Petrik, Application of Beneish M-Score on Selected Financial Statements. Bezpecne Slovensko A Europska Unia, Slovakia Univ. Secur. Manag. Kosice, 1, pp. 307–312 (2016). [Google Scholar]
  2. M. Ansori and S. Fajri, Pendeteksian Kecurangan Laporan Keuangan Menggunakan Rasio Keuangan Dengan Umur Perusahaan dan Ukuran Perusahaan Sebagai Variabel Kontrol, J. Appl. Manag. Account., 2, pp. 141–159 (2018). [Google Scholar]
  3. Bursa Efek Indonesia, Panduan IPO (Go-Public) https://www.idx.co.id/Portals/0/StaticData/Information/ForCompany/Panduan-Go-Public_Dec-2015.pdf. [Accessed: 06-Aug-2021] (2015) [Google Scholar]
  4. R. M. Mbona and K. Yusheng, Financial Statement Analysis: Principal Component Analysis (PCA) Approach Case Study on China Telecoms Industry, Asian J. Account. Res., 4, pp. 233–245 (2019). [CrossRef] [Google Scholar]
  5. S. Wong and S. Venkatraman, Financial Accounting Fraud Detection Using Business Intelligence, Asian Econ. Financ. Rev., 5 (2015). [Google Scholar]
  6. W. S. Albrecht, C. O. Albrecht, C. C. Albrecht, and M. F. Zimbelman, Fraud Examination, 4th ed. New York: South-Western Cengage Learning (2012). [Google Scholar]
  7. S. Santosa and J. Ginting, Evaluasi Keakuratan Model Beneish M-Score Sebagai Alat Deteksi Kecurangan Laporan Keuangan (Kasus Perusahaan Pada Otoritas Jasa Keuangan di Indonesia), Maj. Ilm. Bijak, 16, pp. 75–84 (2019). [CrossRef] [Google Scholar]
  8. N. Omar, Z. A. Johari, and M. Smith, Predicting Fraudulent Financial Reporting Using Artificial Neural Network, J. Financ. Crime, 24, pp. 362–387 (2017). [CrossRef] [Google Scholar]
  9. N. Lotfi and A. A. Chadegani, Detecting Corporate Financial Fraud Using Beneish M-score Model, Int. J. Financ. Manag. Account., 2, pp. 29–34 (2018). [Google Scholar]
  10. S. H. Nia, Financial Ratios Between Fraudulent and Non-Fraudulent Firms: Evidence from Tehran Stock Exchange, J. Account. Tax., 7, pp. 38–44 (2015). [CrossRef] [Google Scholar]
  11. ACFE, Report to The Nations 2020 Global Study on Occupational Fraud and Abuse https://www.acfe.com/report-to-the-nations/2020/. [Accessed: 09-Aug-2021] (2020) [Google Scholar]
  12. H. R. Talab, H. H. Flayyih, and S. I. Ali, Role of Beneish M-score Model in Detecting of Earnings Management Practices: Empirical Study in Listed Banks of Iraqi Stock Exchange, Int. J. Appl. Bus. Econ. Res., pp. 287–302 (2017). [Google Scholar]
  13. S. Repousis, Using Beneish Model to Detect Corporate Financial Statement Fraud in Greece, J. Financ. Crime, 23, pp. 1063–1073 (2016). [CrossRef] [Google Scholar]
  14. Tarjo and N. Herawati, Application of Beneish M-Score Models and Data Mining to Detect, Procedia - Soc. Behav. Sci., pp. 924–930 (2015). [Google Scholar]
  15. B. Haralayya, Ratio Analysis at NSSK Bidar, Iconic Res. Eng. J., 4, pp. 170–182 (2021). [Google Scholar]
  16. E. F. Zainudin and H. A. Hashim, Detecting Fraudulent Financial Reporting Using Financial Ratio, J. Financ. Report. Account., 14, pp. 266–278 (2016). [CrossRef] [Google Scholar]
  17. H. Ramadhan, & I. Laksito, Peran Rasio Keuangan Sebagai Alat Analisi Untuk Mendeteksi Kecurangan Pelaporan Keuangan, Diponegoro J. Account., 8, pp. 1–14 (2019). [Google Scholar]
  18. W. Milasari and D. Ratmono, Pendeteksian Fraudulent Financial Reporting (FFR) Menggunakan Rasio-Rasio Keuangan, Diponegoro J. Account., 8, pp. 1–10 (2019). [Google Scholar]
  19. R. I. Haqqi, M. N. Alim, and Tarjo, Kemampuan Rasio Likuiditas dan Profitabilitas Untuk Mendeteksi Fraud Laporan Keuangan, J. Audit. Financ. Forensic Account., 3, pp. 31–42 (2015). [Google Scholar]
  20. H. Dalnial, A. Kamaluddin, Z. M. Sanusi, and K. S. Khairuddin, Accountability in financial reporting: detecting fraudulent firms, Procedia Soc. Behav. Sci., 145, pp. 61–69 (2014). [CrossRef] [Google Scholar]
  21. A. B. Wimardana and A. Nurbaiti, Pengaruh Financial Stability, Financial Leverage, Rasio Capital Turnover, dan Ineffective Monitoring Terhadap Kecurangan Pelaporan Keuangan, Proceeding Manag., 5, pp. 3382–3391 (2018). [Google Scholar]
  22. D. Iswati, M. Nindito, and A. Zakaria, The Effect of Internal Financial Indicators on the Tendency of Accounting Fraud (A Case of Companies Listed in Indonesia Stock Exchange), J. Din. Akunt., 9, pp. 123–131 (2017). [Google Scholar]

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