Clustering Data Siswa Menggunakan Metode K-Means Untuk Mengetahui Tingkat Prestasi Akademik Di SMK Negeri 2 Kota Bengkulu

Abstract

SMK Negeri 2 of Bengkulu City is one of the State Vocational High Schools in Bengkulu City that continues to strive to improve the quality of its students' academic evaluation. So far, the assessment of student academic achievement still refers to the average value. The school sometimes has difficulty in seeing student development and providing appropriate student motivation based on the results of the level of student academic achievement that has been obtained. Clustering student data using the K-Means Method in determining the level of academic achievement at SMK Negeri 2 of Bengkulu City can provide information on the level of student academic achievement in each subject which is divided into 3 groups, namely high, medium and low levels of academic achievement and can help teachers monitor student academic development, identify student learning patterns, and provide appropriate interventions according to the needs of each group. In order to facilitate the process of clustering student data to determine the level of academic achievement using the k-means method, a desktop-based application was built using the Visual Basic .Net programming language. In addition, this application also contains graphic visuals of the grouping results as output from the application. Based on the test data used, on the grade X Indonesian Language subject data for the Even Semester of the 2022/2023 Academic Year of the Mechanical Engineering Expertise Program of 23 students, the results showed that the high level of academic achievement (Cluster C1) was 7 students, the moderate level of academic achievement (Cluster C2) was 9 students, and the low level of academic achievement (Cluster C3) was 7 students