Implementation of K-Means and TOPSIS Algorithm for Determining High School Student Majors - Yunita Yunita; Desty Rodiah; Putri Eka Wahyuni; Junia Kurniati; Dama Putra Sarpanda (Journal of Embedded Systems, Security and Intelligent Systems, 2025)
This study focuses on the implementation of the K-means algorithm to assist high school students in selecting majors that align with their interests and skills. Utilizing a dataset of 231 grade X students from 2022, the K-means algorithm successfully formed two distinct clusters. The results indicated an accuracy of 81.81% for the K-means clustering process, recall of 81.75%, precision of 77.87%, and specificity of 81.75%. Following this, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was applied to rank the students within each cluster based on various weighted criteria. The TOPSIS method achieved a final ranking accuracy of 80.9%. The findings demonstrate the effectiveness of combining K-means and TOPSIS in facilitating informed decision-making for students regarding their academic paths.