Implementation of K-Means Clustering on High School Students Management

Authors

  • Anggriani Dwi Kartina STIKOM Tunas Bangsa Pematangsiantar, Sumatera Utara
  • M. Safii AMIK Tunas Bangsa Pematangsiantar, Sumatera Utara

Keywords:

Grouping, data mining, Clustering, k-means, High School Students

Abstract

The quality of national education and teaching needs to be monitored continuously in every stage and step of educational activities. The monitoring is intended as an effort to control the quality of education and furthermore as a guarantee of the quality of education. Therefore, a method is needed to facilitate the grouping of high school student data. With the k-means clustering approach, the division of student groups can be done based on the national final exam scores. In this study, students were clustered using the K-Means algorithm. By using K-Means, it aims to facilitate the grouping of the highest and lowest Pemtangssiantar High School students. The result is a picture that shows the grouping of students based on national final exam scores.

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Published

2021-10-14

How to Cite

Kartina, A. D. ., & Safii, M. . (2021). Implementation of K-Means Clustering on High School Students Management. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 1(1), 15–21. Retrieved from https://ioinformatic.org/index.php/JAIEA/article/view/47