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All Journal Journal of Accounting Auditing and Business
Devianti Yunita
Universitas Padjadjaran
Economics, Econometrics & Finance Social Sciences

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Detecting Fraudulent Financial Reporting Using Artificial Neural Network Meutia Riany; Citra Sukmadilaga; Devianti Yunita
Journal of Accounting Auditing and Business Vol 4, No 2 (2021): July Edition
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jaab.v4i2.34914

Abstract

This research aims to examine whether Artificial Neural Network (ANN) method can detect fraudulent financial reporting and whether firms are indicated to commit fraudulent financial reporting. The population in this research are firms listed on the Indonesia Stock Exchange in 2019 and companies that are confirmed to have committed fraudulent financial reporting. In total, 506 data sets were obtained through the purposive sampling technique. The data used in this research were obtained from financial statements. ANN method is used as the data analysis method in this research. Ten variables were used as fraud risk indicators to detect fraudulent financial reporting using ANN. Findings indicate that the developed ANN model can detect fraudulent financial reporting in financial statements. The findings of this research contribute to the literature on methods of detecting indications of financial statement fraud and that it can also be used to assist the auditor's role in detecting material misstatements attributable to fraud
Co-Authors Citra Sukmadilaga Meutia Riany