ANALISIS PENGELOMPOKAN JADWAL MENGAJAR GURU DI SMKN 1 STABAT MENGGUNAKAN METODE K-MEANS CLUSTERING

ANALISIS PENGELOMPOKAN JADWAL MENGAJAR GURU DI SMKN 1 STABAT MENGGUNAKAN METODE K-MEANS CLUSTERING, K-Means Clustering, Teaching Load, Teacher Schedule, Data Clustering, SMKN 1 Stabat...

Author: SULIS SUTIONO
Date: 2025
Keywords: K-Means Clustering, Teaching Load, Teacher Schedule, Data Clustering, SMKN 1 Stabat
Type: Jurnal
Category: penelitian

This study aims to analyze the distribution of teaching load of teachers at SMKN 1 Stabat using the K-Means Clustering method. The main problem faced is the imbalance in the number of teaching hours between teachers which can affect the effectiveness of teaching and learning activities. The data used is the total weekly teaching hours of each teacher, which is taken from the document on the distribution of teaching tasks for the even semester of the 2024/2025 academic year. The K-Means method is used to group teachers into three categories of teaching load: light, medium, and heavy. The grouping process is carried out by determining the number of clusters (K = 3), initializing the centroid, calculating the distance of each data to the centroid, and updating the position of the centroid until the results are stable. The final results show that most teachers are included in the medium load cluster, while a small number are in the light and heavy categories. This shows that the distribution of the teaching load is not yet completely even. The application of K-Means has been proven to be able to provide an analytical picture of the distribution of teacher work, as well as support data-based decision making in education management.

Files:
Tidak ada data !

Collections:
Digital Library UNPAB