Pengelompokan Provinsi di Indonesia Berdasarkan Indikator Pendidikan Menggunakan Metode K-Means Clustering

Grouping Provinces in Indonesia Based on Education Indicators Using the K-Means Clustering Method

  • Mindi Richia Putri University of Mataram
  • Gibran Satya Nugraha Dept Informatics Engineering, University of Mataram
  • Ramaditia Dwiyansaputra Dept Informatics Engineering, University of Mataram
DOI: https://doi.org/10.29303/jcosine.v7i1.509
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Abstract

The education level of the Indonesian people has improved, but has not yet reached the entire population. The educational disparity that occurs between economic groups is still a problem and widens as the level of education increases. The education gap is also still high when compared between regions. Quality learning also has not run optimally and evenly between regions. Accurate and complete information is needed as a reference in planning and determining the right strategy in facing development challenges in the education sector. This information is expected to explain the current condition and situation of education development in Indonesia. This study aims to group provinces in Indonesia based on educational
indicators using the K-Means method. The data and parameters used are based on a portrait of education statistics in Indonesia in 2020. This study shows that clustering produces the best cluster quality at K=3 based on the Silhouette Coefficient

Published
2023-06-30
Section
Intelligent System and Computer Vision