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.