Clustering Students Level of Understanding of Programming Language Courses Using the K-Means Algorithm

Ramadana, Noval
Yani Maulita
Sembiring, Hermansyah

Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Vol. 4 No. 1 (2024): October 2024

This study aims to categorize students based on their level of understanding of programming language courses using the K-Means algorithm. Students often experience difficulties in understanding the basic concepts of programming languages, which can affect their ability to solve programming problems. Using data obtained from questionnaires filled out by STMIK Kaputama Binjai students, this study analyzed variables such as attendance rate, learning interest, and level of understanding. The analysis results show the existence of patterns and relationships between these variables, which can be used to identify groups of students who have a good, poor, or no understanding of the course. This research is expected to provide input for educational institutions in designing learning strategies that are more effective and attractive to students.