K-Means and Naive Bayes Algorithms for Evaluation of Education Personnel Performance Based on SPMI Standards - Wahyudi, Eko; Wijaya, Rian Farta; Khairul , Khairul (Politeknik Ganesha Medan, 2024)
This research compares the K-Means and Naive Bayes algorithms in evaluating the performance of educational staff based on SPMI standards at STMIK Triguna Dharma. The main objective is to identify the effectiveness of the two algorithms in grouping performance evaluation data and determine the advantages and disadvantages of each method. Primary data was obtained through surveys and interviews, while secondary data came from institutional archives. The K-Means algorithm shows 100% accuracy with the ability to group educational staff into very good, good, quite good, poor and poor performance categories. Meanwhile, the Naive Bayes algorithm shows 91% accuracy, with 100% precision results for the