Penerapan Metode K-Means Dalam Pengelompokan Data Siswa Berdasarkan Masalah Akademik Di SMA Negeri Selangit - Chindy Asher; Jhoanne Fredricka; Rizka Tri Alinse (Jurnal Media Infotama, 2025)
Selangit State High School does not yet have a system that can help identify students' academic problems. Until now, the school has only manually recorded each student's disciplinary violations as a point system by observing the violations committed by students, and at the end of the semester, all violation points are calculated. However, this process takes a considerable amount of time, as each student's violation points must be calculated individually, resulting in a lengthy process to determine the appropriate sanctions for each student. The application of the k-means method in grouping student data based on academic issues at Selangit State Senior High School can help the school obtain more specific information regarding students' academic issues and can be used as a benchmark in assisting with evaluations and counseling for students grouped based on academic issues. Based on the test data used in the odd semester of the 2024/2025 academic year, involving 30 students who committed violations, the results showed that cluster C1 had 12 students with sanctions in the form of reprimands, cluster C2 had 10 students with written warnings, cluster C3 had 0 students with suspension warnings, cluster C4 had 5 students with disciplinary action, and cluster C5 had 3 students.