PENERAPAN ALGORITMA K-MEANS DALAM KLASIFIKASI JUMLAH PENDUDUK JAKARTA SELATAN

Application of the K-Means Algorithm in Population Classification South Jakarta

  • Reynold Julian Tamba Universitas Singaperbangsa Karawang
  • Aries Suharso Universitas Singaperbangsa Karawang
  • Purwantoro Purwantoro Universitas Singaperbangsa Karawang

Abstract

This research is a case study conducted at the Directorate General of Population and Civil Registration with the aim of grouping the population based on sub-district and gender, and the method used is the K-Means algorithm. The evaluation results using the silhouette coefficient method show that K-Means is the best algorithm because it obtained a value of 0.7774399276167493. In this study, there were 39 types of population density analyzed, of which 6 were classified as low (cluster 0), 20 were in the middle group (cluster 1), and 8 were middle group (cluster 2), and 6 were the highest (cluster 3). This research makes an important contribution in determining the amount of increase or decrease in population density each year.

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Published
2024-10-04
How to Cite
[1]
R. Tamba, A. Suharso, and P. Purwantoro, “PENERAPAN ALGORITMA K-MEANS DALAM KLASIFIKASI JUMLAH PENDUDUK JAKARTA SELATAN”, Jurnal Informasi dan Komputer, vol. 12, no. 02, pp. 134-136, Oct. 2024.