Implementasi Metode K-Means Clustering Sebagai Penentu Kelompok Belajar di SMA


  • Alfi Nidaul Khasanah Universitas Nahdlataul Ulama Blitar, Blitar, Indonesia
  • Vion Age Tricahyo Universitas Nahdlataul Ulama Blitar, Blitar, Indonesia
  • Muhammat Maariful Huda * Mail Universitas Nahdlataul Ulama Blitar, Blitar, Indonesia
  • (*) Corresponding Author
Keywords: Studi Group; Learning Style; K-Means; Data Mining

Abstract

The way that students study has a big impact on how well they comprehend and retain the material. By creating uniform study groups according to students' learning preferences, this study seeks to maximize the learning process. It is anticipated that this study would use the K-Means Clustering Method to determine each student's preferred method of learning, which may be divided into three categories: kinesthetic, auditory, and visual. In this study, the K-Means technique is used to cluster 68 data points. Four academic value factors are added to the questionnaire, and testing is conducted by comparing the usage of three variables: the academic value of the choice of math, science, and English language. The results of the silhoutte test for three variables showed that 32 students were in cluster 1, 25 students were in cluster 2, and 11 students were in cluster 3. On the other hand, the results of the silhoutte test on four variables showed that there were 26 mahasiswa in cluster 1, about 11 in cluster 2, and approximately 36 in cluster 3. The study's findings indicate that using three variables results in three groups with different numbers of participants, while using four variables results in a somewhat different distribution of groups. Pembentukan kelompok belajar based on the aforementioned study's results is expected to help teachers in guiding siswa learners.

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Article History
Submitted: 2025-01-06
Published: 2025-01-28
Abstract View: 31 times
PDF Download: 39 times
How to Cite
Khasanah, A., Tricahyo, V., & Huda, M. (2025). Implementasi Metode K-Means Clustering Sebagai Penentu Kelompok Belajar di SMA. Journal of Information System Research (JOSH), 6(2), 1283-1291. https://doi.org/10.47065/josh.v6i2.6631
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