ALGORITMA NAIVE BAYES UNTUKMEMPREDIKSI STATUS PENGAJUAN KREDIT KEPEMILIKAN RUMAH

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dc.contributor.authorAndriano, Andriano
dc.contributor.supervisorHarison, Harison
dc.date.accessioned2023-05-05T03:22:05Z
dc.date.available2023-05-05T03:22:05Z
dc.date.issued2023-02
dc.description.abstractThis 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.sponsorshipFakultas Matematika dan Ilmu Pengetahuan Alam Universitas Riauen_US
dc.identifier.citationPerpustakaanen_US
dc.identifier.otherElfitra
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/10981
dc.language.isoenen_US
dc.publisherElfitraen_US
dc.subjectStatus of housing loan applicationsen_US
dc.subjectnaïve bayes algoritmen_US
dc.subjectposterioren_US
dc.subjectconfusion matrixen_US
dc.titleALGORITMA NAIVE BAYES UNTUKMEMPREDIKSI STATUS PENGAJUAN KREDIT KEPEMILIKAN RUMAHen_US
dc.typeArticleen_US

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