ALGORITMA NAIVE BAYES UNTUKMEMPREDIKSI STATUS PENGAJUAN KREDIT KEPEMILIKAN RUMAH

Andriano, Andriano

Home
→
UR - Student Paper Degree
→
Faculty of Mathematics and Natural Sciences
→
Mathematics
→
View Item

dc.contributor.author	Andriano, Andriano
dc.date.accessioned	2023-05-05T03:22:05Z
dc.date.available	2023-05-05T03:22:05Z
dc.date.issued	2023-02
dc.identifier.citation	Perpustakaan	en_US
dc.identifier.other	Elfitra
dc.identifier.uri	https://repository.unri.ac.id/handle/123456789/10981
dc.description.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%.	en_US
dc.description.provenance	Submitted by wahyu sari yeni (ayoe32@ymail.com) on 2023-05-05T03:22:05Z No. of bitstreams: 1 Andriano_compressed.pdf: 184853 bytes, checksum: 7c93093408a1c02722f0cdc2ac62de65 (MD5)	en
dc.description.provenance	Made available in DSpace on 2023-05-05T03:22:05Z (GMT). No. of bitstreams: 1 Andriano_compressed.pdf: 184853 bytes, checksum: 7c93093408a1c02722f0cdc2ac62de65 (MD5) Previous issue date: 2023-02	en
dc.description.sponsorship	Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Riau	en_US
dc.language.iso	en	en_US
dc.publisher	Elfitra	en_US
dc.subject	Status of housing loan applications	en_US
dc.subject	naïve bayes algoritm	en_US
dc.subject	posterior	en_US
dc.subject	confusion matrix	en_US
dc.title	ALGORITMA NAIVE BAYES UNTUKMEMPREDIKSI STATUS PENGAJUAN KREDIT KEPEMILIKAN RUMAH	en_US
dc.type	Article	en_US
dc.contributor.supervisor	Harison, Harison