Performance Analysis of Islamic Banks in Indonesia Using Machine Learning

Abstract

This study aims to examine several factors that influence the performance of Islamic banks in Indonesia by using the variables Return On Assets (ROA), Operating Expenses for Operating Income (BOPO), Capital Adequacy Ratio (CAR), Non Performing Financing (NPF), Financing to Deposit Ratio (FDR) and Potential Losses (PK). The data used in the study takes secondary data from the website of the Financial Services Authority (OJK) from the recapitulation of reports from Islamic banks throughout Indonesia, data taken from 2011 to 2020 which is a combination of Time series and cross section data. The analysis technique used is machine learning with multiple linear regression. The results of the study after being calculated using SPSS, the t table value is 2.776 and the F table value is 5.05. The final result is the hypothesis (H6) is accepted, which means that the variables X1, X2, X3, X4, X5 have a simultaneous effect on Y. Then the ROA value simultaneously influenced by the value of BOPO, CAR, NPF, FDR AND PK..