Andriano, Andriano2023-05-052023-05-052023-02PerpustakaanElfitrahttps://repository.unri.ac.id/handle/123456789/10981This 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%.enStatus of housing loan applicationsnaïve bayes algoritmposteriorconfusion matrixArticle