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All Journal Jurnal Akademik Pengabdian Masyarakat Jurnal Publikasi Ilmu Komputer dan Multimedia
Riska Kherani
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Computer Science & IT Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Social Sciences

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Pembentukan Kelompok Belajar Efektif Berbasis Algoritma Clustering untuk Meningkatkan Kualitas Pembelajaran di SD Negeri Ganrang Jawa II Muhammad Ikhwan Mardin; Sigrid Tamriesfatno; La Ode Muh. Armadi AM; Sarwono Sarwono; Muhamad Irwin Syawal; Riska Kherani; Muhammad As'ad; Sarni Alex Sandra
JURNAL AKADEMIK PENGABDIAN MASYARAKAT Vol. 4 No. 1 (2026): Januari
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/japm.v4i1.8926

Abstract

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.
Penerapan Metode Clustering dengan Algoritma K-Means untuk Pengelompokkan Data Sekolah Menengah di Kabupaten Muna Barat Sigrid Tamriesfatno; Riska Kherani; Sarwono Sarwono
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 4 No. 2 (2025): Mei: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v4i2.4180

Abstract

Improving the quality of education requires a comprehensive understanding of the conditions and characteristics of each educational institution. West Muna Regency has various secondary schools with diverse profiles and challenges. Until now, school grouping has often been done manually, which does not always accurately reflect the overall characteristics of the data. This study aims to cluster secondary schools in West Muna Regency using the K-Means algorithm as a clustering method to identify hidden patterns in school data, such as the number of students, teachers, staff, facilities, and location. The research method involves several stages, including data collection, method analysis, software implementation, and cluster testing. The clustering results produced three school clusters with different characteristics. Cluster 1 consists of schools with the most complete resources, Cluster 2 includes the largest number of schools with varying resources, and Cluster 3 represents schools with moderate conditions. These findings are expected to serve as a basis for formulating more targeted educational policies, ensuring equitable distribution of resources, and improving the quality of education in West Muna Regency.
Co-Authors La Ode Muh. Armadi AM Muhamad Irwin Syawal Muhammad As'ad Muhammad Ikhwan Mardin Sarni Alex Sandra Sarwono Sarwono Tamriesfatno, Sigrid