Model Fraud Pentagon Dalam Mendeteksi Kecurangan Laporan Keuangan Perusahaan Yang Terdaftar Pada Indeks IDX30 Tahun 2015-2019

Abstract

The objective of this study is to examine and assess the Fraud Pentagon model's ability to detect false financial statements in firms that have consistently been included in the IDX30 index from 2015 to 2019. All of the information utilized is secondary and pertains to the company's yearly data. The population is made up of firms that were listed on the IDX30 index between 2015 and 2019, with a sample size of 65 entities. The study variables that have been determined are analyzed using logistic regression in data analysis. From 2015 to 2019, ACHANGE, LEVERAGE, BDOUT, RECEIVABLE, AUDCHANGE, DCHANGE, TATA and CEOPICT all had a simultaneous influence on financial statement fraud in businesses in the IDX30 index. In addition, partial financial stability (ACHANGE) and total accruals have an impact on financial statement fraud (TATA). LEVERAGE, BDOUT, RECEIVABLE, AUDCHANGE, DCHANGE, and CEOPICT had no influence on the false financial statements of firms in the IDX30 index from 2015 to 2019.