PENENTUAN KELAYAKAN KREDIT DENGAN ALGORITMA NAÏVE BAYES CLASSIFIER: STUDI KASUS BANK MAYAPADA MITRA USAHA CABANG PGC
ABSTRACT: In analyzing a
credit sometimes a less accurate credit officer in credit analysis, so that it
can lead to increased bad debts. Classification data mining algorithms are
widely used to determine the credit worthiness of one Naive Bayes classifier,
NBC superior in increasing the value of high accuracy but weak in the selection
of attributes. After testing Naive Bayes classifier algorithm the results
obtained is Naive Bayes classifier algorithm produces an accuracy of 89.33% and
AUC values for 0.955.
Penulis: Nia Nuraeni
Kode Jurnal: jptkomputerdd170324
