Published: 2025-01-01

Analisis Clustering Penyakit Menular pada Manusia di Jakarta Timur Menggunakan Algoritma K-Means

DOI: 10.35870/jtik.v9i1.3007

Muhammad Arya Ramadhan, Edhy Poerwandono, Yuma Akbar, Aditya Zakaria Hidayat
  • Muhammad Arya Ramadhan: Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika , Affiliation name not available , Indonesia
  • Edhy Poerwandono: Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika , Affiliation name not available , Indonesia
  • Yuma Akbar: Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika , Affiliation name not available , Indonesia
  • Aditya Zakaria Hidayat: Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika , Affiliation name not available , Indonesia
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Abstract

Humans are highly susceptible to various diseases without realizing their causes. The high incidence of infectious diseases in East Jakarta requires an analysis of distribution patterns to determine intervention priorities. This study aims to identify clusters of infectious diseases in East Jakarta, helping authorities plan effective prevention and treatment strategies. Data on infectious disease cases were obtained from the Central Statistics Agency of DKI Jakarta. The K-Means algorithm was used to cluster data based on variables such as period, region, type of disease, and number of cases. The results indicate several main clusters with distinct characteristics that can serve as a foundation for targeted strategies. From 2018 to 2021, diarrhea was predominant, making up 84.14% of cases in 2018 and 81.97% in 2019, pneumonia accounted for 32.92% in 2020, and TB Paru 33.63% in 2021. In conclusion, the K-Means algorithm effectively clusters infectious disease data and provides useful insights into disease distribution in East Jakarta, improving the impact of data-driven health programs.

Keywords

K-Means Algorithm ; Clustering ; Infectious Diseases ; East Jakarta ; Data Analysis

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How to Cite

Ramadhan, M. A., Poerwandono, E., Akbar, Y., & Hidayat, A. Z. (2025). Analisis Clustering Penyakit Menular pada Manusia di Jakarta Timur Menggunakan Algoritma K-Means. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 9(1), 52-58. https://doi.org/10.35870/jtik.v9i1.3007
Article Information

This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.

  • Issue: Vol. 9 No. 1 (2025)

  • Section: Computer & Communication Science

  • Published: %750 %e, %2025

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Author Biographies
Muhammad Arya Ramadhan
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibu Kota Jakarta, Indonesia

Edhy Poerwandono
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibu Kota Jakarta, Indonesia

Yuma Akbar
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibu Kota Jakarta, Indonesia

Aditya Zakaria Hidayat
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibu Kota Jakarta, Indonesia

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