Does the Covid-19 pandemic affect financial distress of sharia commercial banks in Indonesia? (analysis using artificial neural network)

This study aims to determine whether there is a role for the current ratio value, return of equity, operating costs of operating income, company size, and the COVID-19 pandemic in the prediction model of financial distress for Islamic Commercial Banks (BUS) in Indonesia. This study uses a quantitative approach with non-parametric statistical methods artificial neural network backpropagation algorithm. The sample used is the financial report data of Islamic Commercial Banks (BUS) quarterly in 2015-2020 with the proportion of training data and testing data of 90%:10%, 80%:20%, and 70%:30%. The results of this study indicate the best model for predicting financial distress with the highest accuracy of 92.7% and AUC of 92.5%, which is included in the excellent classification. Of the five determinants of financial distress used, return of equity and company size contributed the most then BOPO, Current ratio and pandemic COVID-19 for the last. The COVID-19 pandemic only contributed 5. %. It confirms that Islamic banks in Indonesia can survive during the COVID-19 pandemic. Furthermore, Islamic banks need to maintain a stable return on equity and company size to minimize the chances of Islamic banks experiencing financial distres