Clustering the K-means Algorithm with the Approach to Student Interpersonal Communication Patterns in Selecting Secondary Schools

Abstract

This research aims to understand students' communication patterns in choosing secondary schools by identifying existing group patterns, and understanding the factors that influence students' decisions in choosing secondary schools. Using the k-means algorithm clustering method, the dataset was obtained from student data, psychological test scores and interpersonal communication in three grade 9 junior high schools in West Jakarta. The dataset obtained was 317, the results of data clearing were 259 students who were eligible to be tested. The results of tests carried out with 4 clusters show an accuracy value close to 0, with cluster 2 having a value of -0.150. The results show that students who choose a secondary school based on their psychological test results and interpersonal communication between parents, homeroom teachers and the school are the dominant values in the continuity of selecting a senior secondary school.