Implementasi Aplikasi Web Pemilihan Kelas Berdasarkan Minat Menggunakan Algoritma K-Means Clustering
DOI:
https://doi.org/10.35870/jtik.v9i1.3165Keywords:
K-Means Clustering, Class Recommendation, Web ApplicationAbstract
Giki High School has a large number of 10th grade students and the need to provide class recommendations based on student interests in current subjects is done conventionally. This study aims to help schools make more informed decisions in class selection. This study implements a web application. The implementation of the category selection web application was created using the K-means Clustering algorithm and integrated into the web using Tkinter as the standard GUI library for Python. This implementation goal is to make school life easier to determine class recommendations for students. Results of the K-Means algorithm produce 4 clusters: Cluster 1 (Indonesian, Social Studies, and Mathematics), Cluster 2 (English), Cluster 3 (Indonesian and Science), Cluster 4 (English and Science) with the Silhouette Score results giving a score of 0.6233 which indicates that the score calculation is at 0 that the data point is the center of each cluster.
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