FAKTOR-FAKTOR PENYEBAB FINANCIAL DISTRESS DIUKUR MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK PADA PERBANKAN SYARIAH DIINDONESIA

Eka Sri Wahyuni (Universitas Islam Negeri Fatmawati Bengkulu)

Jurnal Akuntansi dan Pajak
Vol 23, No 1 (2022): JAP : Vol. 23, No. 1, Februari 2022 - Juli 2022

This study aims to determine the factors that affect financial distress measured using the artificial neural network method in Islamic banking in Indonesia, where this study is a quantitative study that uses a data processing tool, namely SPSS version 20. The results of this study show that what affects financial distress when measured using the artficial neural network method is only operating income operating costs (BOPO) which have a significant positive influence while for other facto-factors such as Non Performing Financing (NPF), Financing to Deposit Ratio (FDR) does not have a significant positive influence, after being tested together the three factors that affect financial distress can produce a positive and significant influence.