Sistem Pendukung Keputusan Penentuan Kelayakan Penangguhan Kredit Nasabah menggunakan Naïve Bayes

Aldy Sudrajat, Neni Mulyani, Nasrun Marpaung


The COVID-19 (Corona Virus Disease 2019) pandemic is still spreading until 2022, so in responding to this, PT Adira Finance provides an opportunity to suspend credit installment payments to nasakabah. In order not to cause installments and defaults (breaking promises) it is necessary to have a decision support system to determine the creditworthiness of these customers. The purpose of this study is to build a decision support system to determine the feasibility of solicitation to customers using the naïve bayes method. The model used to build this system is the System Development Life Cycle (SDLC) with stages of analysis, design, testing, and implementation. The sample or training data used in this study was 20 customers. Meanwhile, the technique used to determine the feasibility of customer suspension uses naïve bayes by looking at the prior and conditional probability values of each criteria. Our findings result in a customer eligibility decision support system with the naïve bayes method is appropriate and accurate. So that with this system, it can be used as a consideration to make decisions by the manager of PT Adira Finance to determine whether or not customers are eligible to receive a credit suspension.


classification; decision support system; naïve bayes; suspension of credit

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