Mendeteksi Kecurangan Laporan Keuangan Menggunakan Model Beneish - Irsutami Irsutami; Rizky Sapriadi (Pusat P2M Politeknik Negeri Batam, 2020)
This study aimed to determine the effect of eight Beneish variables on earnings management in detecting fraudulent financial statements in property, real estate and building construction companies listing on the Indonesia Stock Exchange in 2014 - 2018. The population in this study is 80 companies in property, real estate and building construction sector. The sampling technique uses purposive sampling. The method of data collection used archival data collection techniques in the database. Data analysis used descriptive analysis using the Beneish ratio index, the classic assumption test and simple linear regression analysis. The results showed that DSRI (DaysoSalesoinoReceivableoIndex), SGI (SalesoGrowthoIndex), DEPI (DepreciationoIndex), TATA (TotaloAccrualotooTotal AssetsoIndex), and LVGI (LeverageoIndex) variables significantly influence earnings management in detecting fraudulent financial statements in sample companies. While the GMI (Gross MarginoIndex), AQI (AssetoQualityoIndex), and SGAI (Selling, GeneraloandoAdministrative Index) no significant effect on earnings management in detecting fraudulent financial statements in sample companies.