Educational data mining for mapping the comprehension of personality subject using K-Means algorithm (case study of SD Insan Mulya)

Wiwiet Herulambang (Universitas Bhayangkara Surabaya, Jawa Timur, Indonesia)
M Mahaputra Hidayat (Universitas Bhayangkara Surabaya, Jawa Timur, Indonesia)
Nabila Amanda Putri (Universitas Bhayangkara Surabaya, Jawa Timur, Indonesia)

Jurnal Mandiri IT
Vol. 11 No. 4 (2023): April : Computer Science and Field.

The government has emphasized the importance of character education since the elementary school (SD) level by providing various subjects as an effort to build personality/character for each student. It is important for teachers and schools to know the level of understanding in their students. This research is for. This study uses the K-Means Clustering Algorithm method to help map students to the level of understanding of the Personality subject. The results of this study indicate that clustering using the K-Means Algorithm method contains 4 effective clusters in mapping the understanding of personality subjects. The result of the percentage of clusterization results with interviews is 89.39% while the percentage of software is 91.70%. The conclusions obtained in this research are the subjects of Moral Education, Religious Education, Citizenship Education are included in the Subjects that can affect the student's personality.