Bayesian Mixture Multinomial Regression Model for Loan Repayment Classification of Village Unit Cooperative - Yusril Izzi Arlisa Amiri, Nur Iriawan, Kartika Fithriasari (International Journal of Advanced Science and Technology, 2020)
Village Unit Cooperative (VUC) is an institute that provides financial services consisting of several sub-businesses, one of which is providing loans. To downplay the danger of non-performing loans, the cooperative must be capable to assess prospective borrowers before a loan decision is required. In this case, loan repayment with its three categories coupled with two types of the installment and interest payment systems is constructed to create a suggested structure of Mixture Multinomial distribution with two components. This construction is used to determine loan repayment of the applicant by using the Bayesian Mixture Multinomial Regression model (BMMRM). The estimating parameter is performed by making an algorithm based on Bayesian Markov Chain Monte Carlo (MCMC) couple with the Gibbs sampling algorithm. The classification performance of loan repayment through the BMMRM is assessed by determining loan repayment classification percentage of the model which is compared with loan repayment classification percentage of the Polytomous Logistic Regression Model (PLRM). The comparative results show that the BMMRM approach gives a higher percentage of loan repayment classification performance than the PLRM.