Fraud Triangle Perspective: Artificial Neural Network Used in Fraud Analysis

Abstract

This study aims to determine the Triangle Perspective: Neural Network Used in Fraud Analysis. Application of the Artificial Neural Network method to investigate and detect fraud in companies. The number of samples used in this study was 102 companies. The population in this study are manufacturing companies listed on the Indonesia Stock Exchange for the 2016-2019 period. The test was carried out using an artificial neural network (ANN) method using the SPSS 25 application. External pressure does not affect fraudulent financial statements, and financial stability significantly affects financial statement fraud. The nature of the industry has a significant effect on financial statement fraud, inventory to sales ratio has a significant effect on financial statement fraud, the ineffective monitoring variable has no significant effect on financial statement fraud, gross profit to total assets has a significant effect on financial statement fraud. Return on assets has no significant effect on financial statement fraud, net profit margin (NPM) has no significant effect on financial statement fraud, firm liquidity (WCTA) has a significant effect on financial statement fraud.