PREDICTION OF LATE INSTALLMENT PAYMENT BASED ON INTEGRATION MODELING CLUSTER ANALYSIS AVERAGE AND WARD LINKAGE WITH SURVIVAL ANALYSIS (CASE STUDY: HOUSE OWNERSHIP LOAN BANK X CUSTOMERS)

Cluster analysis is an exploratory analysis that is used to group objects into several clusters, which clusters have different characteristics. Survival analysis with Extended Cox regression is used when there is a time-dependent predictor variable so that the proportional hazard assumption is not met. This study integrates the two methods. The variables used are Collateral, Character, Capacity, Condition, and Capital (5C), Credit Collectability, and Credit Payment Time. The 5C variable has many indicators. The data used is secondary data obtained from a bank. The purpose of this study was to compare the Extended Cox Regression model based on the integration of Cluster analysis on Ward, and Average linkage with Survival analysis using the Extended Cox Regression method. The results showed that the integrated cluster model in Ward Linkage-based Extended Cox regression was the best method with two clusters formed and the smallest mean squared error value of the model, which was 0.265.