ALGORITMA NAIVE BAYES UNTUKMEMPREDIKSI STATUS PENGAJUAN KREDIT KEPEMILIKAN RUMAH
No Thumbnail Available
Date
2023-02
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Elfitra
Abstract
This study discusses the classification analysis of the status of housing loan applications
(KPR) at one of the banks in Pekanbaru City using the naïve Bayes algorithm. The
purpose of this study is to classify data on the status of mortgage applications at one of
the banks in Pekanbaru City. The results show that the highest posterior value is in the
rejected class. Classify naïve Bayes able to classify data on mortgage application status.
This is shown from the confusion matrix, namely, the accuracy value reaches 50.96%,
the sensitivity is 78.05%, and the specificity is 16.25%.
Description
Keywords
Status of housing loan applications, naïve bayes algoritm, posterior, confusion matrix
Citation
Perpustakaan