Klasterisasi Penempatan Siswa yang Optimal untuk Meningkatkan Nilai Rata-Rata Kelas Menggunakan K-Means

The implementation of learning by teachers can measure the quality schools and students. Schools with diverse student backgrounds need to take strategic steps in managing get optimal outcomes. Good designs techniques motivate students' interest learning. teacher's role is very important create an effective teaching process. Data Mining or also known as Knowledge Discovery Database (KDD) process extracting knowledge from large data find new patterns information. technology used explore existing database. One methods mining clustering K-Means algorithm. This study aims conduct obtain a balanced class composition order improve outcomes seen increasing average score. processed this came main school many 90 students XI Computer Network Engineering Skills Competency at SMKN Negeri 2 Padang Panjang 2020/2021 year. variables processing are scores, parents' income distance where live school. calculation using succeeded grouping into 3 clusters cluster 1 totaled 47 students, 10 33 Each member will be divided evenly groups studying composition. research basis for decision making placements By grade point average, score increased.