This research aims to form a prediction model for BPR bankruptcy in Indonesia. The method used in this research uses logit analysis. The data used is secondary data obtained from published bank reports for the period 2008 - 2019. The population used in this research is BPR in East Java and the sample selection was based on purposive sampling. The initial step of this research is to build a dependent variable prediction model using in-sample, review its validity, then test the validity of the model based on out-of sample data. The research results show that CAR, LDR, CG, NPL, OR and OBS have a significant effect on bankruptcy. Meanwhile, NIM and CR do not have a significant effect on bankruptcy. BPR must pay attention to variables that are indicators of bankruptcy. This research is useful for providing a different perspective in building bankruptcy models, especially in BPR, with methods that have never been done before.
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