Penggunaan Algoritma Naïve Bayes Untuk Menentukan Pemberian Kredit Pada Koperasi Desa

Ika Nurjanah; Jamilah Karaman; Ida Widaningrum; Dyah Mustikasari; Sucipto Sucipto

doi:10.47065/explorer.v3i2.766

Ika Nurjanah Universitas Muhammadiyah Ponorogo, Indonesia
Jamilah Karaman * Universitas Muhammadiyah Ponorogo, Indonesia
Ida Widaningrum Universitas Muhammadiyah Ponorogo, Indonesia
Dyah Mustikasari Universitas Muhammadiyah Ponorogo, Indonesia
Sucipto Sucipto Universitas Nusantara PGRI Kediri, Indonesia

DOI: https://doi.org/10.47065/explorer.v3i2.766

Keywords: Naive Bayes Algorithm; Data Mining; Customer Historical Data; Lending

Abstract

Giving credit to customers is a routine activity carried out by a cooperative, as happened in the Subur Sari Forest Village Community Institution Cooperative (LMDH) in Pudak Wetan Village, Ponorogo Regency. Non-performing or bad loans often occur due to a lack of thorough analysis in the credit granting process. This happens because the management is less careful in determining which applicants are eligible for loans. Therefore, customer eligibility analysis is fundamental in determining whether a customer is eligible or not to get a loan. One way to determine creditworthiness is to use the Naïve Bayes algorithm. This study aims to apply data mining methods to classify eligible, and ineligible customers based on historical customer data in the past then used to predict the feasibility of future customers using the Naïve Bayes algorithm. The results of testing the credit classification system using the black box stated that the system was able to run according to the algorithm and could determine whether or not the customer deserved credit.

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