A Decision Support System for Credit Application Eligibility Using the Naïve Bayes Method
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Abstract
This study aims to build a decision support system for the feasibility of applying for credit at Bank Sumsel Babel Pagar Alam Branch using the Naïve Bayes method. This research is motivated by the high public interest in credit loans, so the submission of credit loan files that make many account officers spend a lot of time looking at the condition of prospective debtors to the field which does not necessarily meet current customer predictions. So many customers also complain because there has been no confirmation from the bank regarding the submission of their credit files. Meanwhile, in addition to surveys to the field, account officers must also prepare disbursement files for debtors who are eligible to receive credit loans. So it is considered necessary to have a system that will assist account officers in improving credit loan services with a decision support system (SPK). In this study, we will use the Naïve Bayes algorithm in predicting the eligibility of prospective debtors. This research will use the Rapid Application Development (RAD) system development method. Testing using the blackbox testing method. The result of this Skripsi is the design of a decision support system for the feasibility of applying for credit at Bank Sumsel Babel Pagar Alam Branch using the Naïve Bayes method.
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