CUSTOMER CREDITWORTHINESS ANALYSIS USING ALGORITHMS (CASE STUDY: KOPERIA)

Abstract

Cooperative management in Koperia (Cooperative Citizens of Komplek Gandaria) to provide credit to customers is still based on process that is not objective and many still have problems. Therefore it is difficult in determining creditworthiness which is often experienced by cooperative management. The problems that arise in the cooperative is the payment of installments that often experience jams because of frequent delinquent. Where if many customers are delinquent in payment it will disrupt the company's financial system. Implementation of data mining in terms of data mining context is expected to provide a solution to determine the extension of creditworthiness to customers, by applying the process of classification on data mining using Algorithm C4.5, using data set attributes, Amount of Income, Total Balance, Amount of Loans, and Needs. The results of this research is to apply C4.5 algorithm to determine the feasibility of lending customers on the cooperative based on the attributes that have been determined to determine how to determine in the process of granting credit with the Attributes of Needs, Number of Loans, Total Income and Amount of Loans.