Penentuan Kelayakan Penerima Pembiayaan Kredit Menggunakan Metode Naive Bayes dan Algoritma C4.5 (Studi Kasus: KSPPS BMT Adil Berkah Sejahtera)

Tri Ardiyanto
Handoyo Widi Nugroho

Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Vol 6, No 1 (2023): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)

Banking provides credit services to facilitate the community in running a business. To minimize risk, banks need to analyze the feasibility of extending credit to customers. This research aims to obtain the best procedure for classifying credit worthiness to customers. The reason for choosing the best method is the method that is appropriate for use in the classification of credit granting with the highest accuracy value. The highest accuracy was selected through a comparison of the c4.5 and naive bayes algorithms. The accuracy results obtained from the c4.5 algorithm with three tests were 91.23% and AUC 0.686 while Naive Bayes produced an accuracy of 89.90% and AUC 0.744 Keywords: Creditworthiness, classification, algorithm c4.5, naive bayes