<![CDATA[The process of determining outstanding students at SDN Baru 06 Pagi has so far been done manually, requiring a relatively long time and potentially resulting in less objective assessments. This research aims to facilitate the school in classifying students as high-achievers and low-achievers at SDN Baru 06 Pagi. Therefore, this research applies the K-Nearest Neighbor (KNN) method as a classification method by comparing test data against training data that has been labeled as high-achieving and low-achieving based on proximity values. The research results indicate that the developed application is capable of assisting the school in determining students' achievement status more effectively, quickly, and objectively. The model's performance evaluation resulted in an accuracy of 85.48%, a precision of 82.69%, a recall of 100%, and an F1-score of 90.53%. Based on these evaluation results, the K-Nearest Neighbor method has excellent performance and is suitable to be applied as a decision support tool in the classification of high-achieving students.]]>
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