Classification Analysis of Student Ability in Learning Using Clustering Method at SMA Tunas Pelita

Authors

  • Nurhayati Program of Technical Information, STMIK Kaputama
  • Juliana Naftali Sitompul Program of Technical Information, STMIK Kaputama
  • Tri Kartika Sari Program of Technical Information, STMIK Kaputama

Keywords:

data mining, k-means, class X average value

Abstract

This study aims to classify the assessment of the learning process at SMA Tunas Pelita Binjai T.A. 2018/2019 based on the average grade X, additional subjects applied technology, and student absenteeism classified using Matlab.The data is processed based on learning grouping as much as 2 clusters with different centroids, namely for cluster 1 the average value of even and odd semesters for class X (85.0), additional subjects of applied technology (86.3) and student attendance (2.4) and cluster 2 the average grades of odd-even semesters for class X (68.2), additional subjects of applied technology (70.3) and student attendance (2.4). In the final result, it can be seen that the grouping of learning at SMA Tunas Pelita Binjai with 100 data can be divided into 2 groups, namely group 1 with 62 data with an average value of odd and even semesters and high additional applied technology and student absenteeism. low grades are classified as students with good grades and group 2 as many as 38 data with an average value of odd, even semesters and low values ​​of applied technology and high student absenteeism belonging to students who have poor grades.

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Published

2021-10-14

How to Cite

Nurhayati, Sitompul, J. N. ., & Sari, T. K. . (2021). Classification Analysis of Student Ability in Learning Using Clustering Method at SMA Tunas Pelita. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 1(1), 9–14. Retrieved from https://ioinformatic.org/index.php/JAIEA/article/view/46