<![CDATA[This community service program aims to form effective student learning groups based on clustering algorithms to improve the quality of learning at SD Negeri Ganrang Jawa II. The main problem faced by teachers is the difficulty in dividing students into learning groups evenly based on academic ability, as well as students’ tendency to choose their own friends when working in groups. These conditions result in unbalanced and less effective learning groups. To address this problem, the K-Means Clustering algorithm is applied to group students based on academic scores, so that each group consists of students with high, medium, and low abilities. The service method includes collecting student academic data, implementing the clustering algorithm, and assisting teachers in applying the learning groups. The results show that the distribution of learning groups becomes more balanced, student interaction increases, and the learning process runs more effectively. Therefore, the application of clustering algorithms can serve as an innovative solution to support collaborative learning strategies in elementary schools.]]>
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