Implementation of Composite Index to Determine Risk Tend to Bank Default at Rural Bank - et. al., Devy M. Puspitasari, (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
This study aims to identify risk tend to bank default using a composite index at rural banks in Indonesia. The method used in this study uses logit. The data used are primary and secondary. Primary data is used when weighting the composite index by respondents who are representatives of banking associations, bank authorities and directors. Secondary data obtained from Bank publication reports during period 2009 - 2018. The population used in this study is rural banks in East Java and sample selection based on purposive sampling. The results showed that NIM, NPL, OR and ROA have significant affect to risk of tend to bank default. Meanwhile, LDR have no significant affect to risk of tend to bank default. Rural bank must pay attention to the variables that are indicators of the risk tend to bank default.This study is useful for providing a different perspective in identifying bank default using a composite index that has never been conducted before.