Citra Kredit is a company engaged in general trading and financing. One of the services at Citra Kredit is a loan with a BPKP guarantee. For companies engaged in data, it is important to be able to select customers so that bad credit does not occur. Citra Kredit has a standard for accepting and rejecting consumers. To determine prospective customers in providing credit, the company analyzes the data of potential customers by a supervisor. The existence of credit analysis is very important in the scope of financial risk, because it is necessary to do an analysis. So, analyzing data on customer data in order to predict the smooth payment by customers is an important thing to do. For this data, data mining can be used, which is an approach to getting useful information from large amounts of data. The data mining algorithm that has the ability to classify and predict is C4.5. The C4.5 algorithm is a decision tree algorithm that can solve the problem of missing values, continuing data and pruning. This study uses 1,153 training data with 91 testing data and uses six attributes. The attributes used include: gender, marital status, tenor, occupation, loan, and stage. This study produces a model that can predict the smoothness of instalment payments using the C4.5 algorithm. From the results of the evaluation using confusion matrix, an accuracy of 79% is obtained.

Keywords: C4.5, Classification, Prediction, Installment Payment