William Dhamawan
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Algoritma K-Means Clustering Pada Pengelompokan Minat Bakat Siswa SMK PGRI 2 Karawang William Dhamawan
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 1 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i1.2469

Abstract

New students have their own choices in choosing a school, but these choices are not always in accordance with their abilities. Making the choice is very important for the desired end result. Vocational High School is a school that consists of several majors that can be chosen by new students according to the interests of students. The school has a policy in determining majors by making interest and aptitude tests. The test is carried out when students register. Data Mining can determine the new student study groups needed by the school. The clustering method with the k-means algorithm is the choice to determine the new student study group. The learning machine used is RapidMiner. Data processing using data mining will produce new student study groups needed by the school.