Prediction System for Credit Eligibility Using C4.5 Algorithm

Abstract

Independent Multipurpose Cooperative, Tasti, Pagar Alam City, currently granting credit, the data collection process for the selection of prospective members and prospective credit recipients is still done manually, so they must come to the cooperative to find out whether it is still eligible to receive credit or not, officers must evaluate the data. is to form a decision tree classification model for creditworthiness in cooperatives. The analytical method with the C4.5 Algorithm, the C4.5 Algorithm is one of the algorithms for performing data mining using data classification techniques. The C4.5 algorithm is used to search for knowledge in the data, by finding the relationship between input variables or criteria attributes with target variables or decision attributes. The resulting knowledge is converted into the form of a decision tree so that it is easy to understand. The C4.5 algorithm was chosen because it can make a decision to be able to predict whether a customer is eligible or not to be given credit. The attribute used is income with specified criteria. The results obtained from this study are predictive information on the feasibility of providing credit to cooperatives using the C4.5 algorithm by getting an accuracy value of 93% with an AUC value of 0.898 where this classification is classified as Good Classification or good.