Implementation of K-Means for Clustering Student Development

Abstract

TK PAUD KB Kasih Ibu Tulin Onsoi is an early childhood education institution independently established by the Sebuku Village Government. This institution evaluates the child’s progress every semester and provides the progress information through report cards. The teacher assesses the development based on the report card value. There is no student clustering to decide which children will be monitored further by emphasizing learning from students who have not yet developed. One method to implement is K-Means clustering. This study used report card data for one semester. Then, analyze the data using K-Means with 4 clusters, namely Not Developed (BB), Starting to Develop (MB), Developing As Expected (BSH) and Very Well Developed (BSB). The implementation of child clustering has succeeded in becoming several clusters with almost the same similarity values. Clustering 38 children's data shows that 13 children are developing very well (BSB), 4 are developing according to expectations (BSH), 8 starting to develop (MB), and 13 are not yet developing (BB).