Developing a Predictive Model About Bankruptcy in the Rural Areas of Indonesia

Abstract

The purpose of this study is to develop a model for predicting bankruptcy in rural areas of Indonesia. The method used in this study uses logit. The data used is auxiliary data obtained from the World Bank publication reports during the period 2009-2018. The population used in this study is a rural bank in East Java, and the sample is based on intentional sampling. The results show that CAR, LDR, CG, NPL, OR and OBS have a significant impact on bankruptcy. NIM and CR have no major impact now. The rural banking industry needs to beware of indicators that indicate bankruptcy or bankruptcy. Banks must implement risk management and meet regulatory capital requirements to be able to resist risks and comply with bank governance rules so that rural banking businesses can generate high returns, thereby affecting resilience and resilience. its existence. This research will help identify banks that may fail in the future based on the variables discussed in this research. The ability to detect failures in the banking environment and distinguish between soundness banks and troubled banks predicts bank failures. As an early warning system, bank supervisors can use it to maintain the sustainability of the rural banking industry, but it has not yet been completed.