Automation of Credit Approval Eligibility Using The Simple Additive Weighting Method At Financial Institutions

Abstract

Cooperatives as financial institutions engaged in has an important role in providing a source of financing for its members. The credit approval eligibility process in cooperatives is often done manually, which can take a long time, is prone to human error and subjectivity in decision making. and subjectivity factors in decision making. The method used method used in this research is the Simple Additive Weighting (SAW) method that is applied in automating the feasibility of credit approval in cooperatives. The criteria used in this research are income, age, credit history, occupation, number of dependents. This method is used with the aim of providing decisions that are more consistent, objective, transparent, and the time it takes is shorter. The result of this study is that customer A gets the highest score of 0.82, so that the customer is declared the most deserving prospective debtor to get credit approval at the cooperative. The results show that the application of the SAW method in the automation of credit approval eligibility has succeeded in increasing time efficiency in the credit approval eligibility assessment process so that it can handle more credit cases efficiently, besides that this method is able to minimize human error, and is able to eliminate the subjectivity factor in decision making. This can increase customer confidence in supporting transparent cooperative operations