<![CDATA[This study aims to optimize the performance of Education personnel in MTsN 1 Labuhanbatu Selatan through the application of Naive Bayes algorithm for performance classification. The performance of Education personnel, including administrative, administrative, and service staff for one school year was analyzed using data involving attributes such as attendance, punctuality, productivity, and work attitude. Naive Bayes algorithm was chosen because of its ability to classify data accurately and efficiently despite the large amount of data. The results showed that the use of this algorithm can produce a more objective, accurate, and data-based evaluation system, as well as provide clearer insights in improving work efficiency and service to teachers and students. The evaluation of the model was conducted using accuracy, precision, recall, and F1-score metrics to ensure that the classification of educational staff performance can be done appropriately. The study also provides recommendations to improve data quality and the use of additional attributes to improve model performance.]]>
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