Classification of Feasibility of Credit for Candidated CS Finance Debtors Using Naïve Bayes Method - Nuraisana; Ellisa Purba (Institute of Computer Science (IOCS), 2020)
CS Finance is one of the central financing institutions in the two-wheeler finance industry. CS Finance, which was founded in 2010 under the name PT Central Santosa Finance. The problem that is often faced is when conducting administrative assessments to determine the right prospective debtor's eligibility. We need a system that can assist CS Finance in determining the feasibility of prospective debtors quickly and precisely. The method used in this research is Naïve Bayes. The data processed is data of prospective debtors. The variables used have been determined based on four attributes, namely character, capacity, capital, and conditions; testing is carried out using Rapidminer software, and the accuracy of the Naïve Bayes algorithm for predicting the feasibility of prospective debtors based on training data shows good performance, namely 80%. Hence, it is feasible for use. To make it easier for users to predict prospective borrowers' creditworthiness, a creditworthiness classification system for prospective debtors has been created in CS Finance using the web-based naïve Bayes method.