Nasution, Nurhamimah2023-08-212023-08-212023-06PerpustakaanElfitrahttps://repository.unri.ac.id/handle/123456789/11126Prediction is an attempt to look at past conditions to predict future conditions. Prediction of student achievement is something that is very important in the world of education that can increase quality graduates. This study aims to implement the Naïve Bayes Classifier Algorithm to predict student achievement for one semester at SMKN 1 Barumun. The data used were 1191 student data, with a ratio of 80% and 20%, with 6 criteria or attributes for student achievement requirements consisting of the average grade of assignments, average midterm scores, average UAS scores, average number of class attendance, average practicum scores and the average attitude value used for the classification process. Tests were carried out using the Confusion Matrix with an accuracy of 96.15%, precision of 94,16% and recall of 100%.enNaïve Bayes Classifier AlgorithmConfusion MatrixPredictionAchievementArticle