Population Density Cluster Analysis in DKI Jakarta Province Using K-Means Algorithm

Authors

  • Amalia Anjani Arifiyanti Universitasi Pembangunan Nasional "Veteran" Jawa Timur, Indonesia
  • Farhan Setiyo Darusman Universitasi Pembangunan Nasional "Veteran" Jawa Timur, Indonesia
  • Brahmantio Widyo Trenggono Universitasi Pembangunan Nasional "Veteran" Jawa Timur, Indonesia
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DOI:

https://doi.org/10.51519/journalisi.v4i3.315

Keywords:

Clustering, Data Mining, Population Density, K-Means

Abstract

This study aims to analyze clusters based on the area and population density of the area and population density of the area in DKI Jakarta Province in 2015 using the data mining method by clustering as the first step in planning for population equality. The subject of analysis in this study is a village located in the province of DKI Jakarta which is recorded based on the area and population density in each sub-district until 2015 with several stages, namely data understanding, data processing or cleansing, cluster tendency assessment, clustering, cluster review. From this study, the results were obtained that the data tended to be clustered because the statistical value of Hopkins was close to the value of 0 and in VAT there was a vague picture of clusters that might be formed. Based on this, cluster creation is carried out using the K-Means Algorithm.  Based on the results, there are 3 clusters formed, namely cluster 0 (not densely populated), cluster 1 (medium population density), and cluster 2 (densely populated). These results can be used as a basis for policy making in population management.

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Author Biographies

  • Farhan Setiyo Darusman, Universitasi Pembangunan Nasional "Veteran" Jawa Timur

    Sistem Informasi, Fakultas Ilmu Komputer

  • Brahmantio Widyo Trenggono, Universitasi Pembangunan Nasional "Veteran" Jawa Timur

    Sistem Informasi, Fakultas Ilmu Komputer

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Published

2022-09-02

Issue

Vol. 4 No. 3 (2022): Journal of Information Systems and Informatics

Section

Articles

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How to Cite

[1]
A. A. Arifiyanti, F. S. Darusman, and B. W. Trenggono, “Population Density Cluster Analysis in DKI Jakarta Province Using K-Means Algorithm”, journalisi, vol. 4, no. 3, pp. 772–783, Sep. 2022, doi: 10.51519/journalisi.v4i3.315.