MODELING THE DISTRIBUTION OF HIV CASES WITH K-MEANS CLUSTERING CASE STUDY OF WEST JAVA PROVINCE

In Indonesia, the problem of HIV/AIDS is a serious concern because the trend of cases tends to increase in several regions, including in West Java Province, 2018 data from the Health Office shows a significant variation in the number of HIV cases among districts and cities in the province, in this journal, a visualization process is carried out using Google Colaboratory (Google Colab) to provide an overview of the distribution pattern of cases based on the results of the K-Means Clustering algorithm. The results showed the existence of three main clusters, namely areas with low, medium, and high numbers of cases. Large cities such as Bandung and Bekasi were in the group with the highest number of cases, while peripheral and rural areas showed lower numbers of cases. This finding is expected to be the basis for formulating more effective health policies, especially in education programs, early detection, and community-based interventions to support the goal of eliminating HIV by 2030, then what can be done is to carry out intervention strategies or steps to prevent the spread of HIV tailored to the risk level of each cluster resulting from clustering analysis. Local governments are expected to utilize the results of this mapping to develop more detailed prevention strategies according to the characteristics of each region.

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Publication Details

Journal
Jurnal Riset Informatika
Published
2025-06-12
DOI
https://doi.org/10.34288/jri.v7i3.374
Primary Topic
Advanced Clustering Algorithms Research
Type
article
Field-Weighted Citation Impact
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article

MODELING THE DISTRIBUTION OF HIV CASES WITH K-MEANS CLUSTERING CASE STUDY OF WEST JAVA PROVINCE

Agustia Hananto, Tukino Tukino, Muhammad Difa Prakoso Fuadi, Fitria Nurafriani
Jurnal Riset Informatika
Advanced Clustering Algorithms Research
article

MODELING THE DISTRIBUTION OF HIV CASES WITH K-MEANS CLUSTERING CASE STUDY OF WEST JAVA PROVINCE

Agustia Hananto, Tukino Tukino, Muhammad Difa Prakoso Fuadi, Fitria Nurafriani
article en

Abstract

In Indonesia, the problem of HIV/AIDS is a serious concern because the trend of cases tends to increase in several regions, including in West Java Province, 2018 data from the Health Office shows a significant variation in the number of HIV cases among districts and cities in the province, in this journal, a visualization process is carried out using Google Colaboratory (Google Colab) to provide an overview of the distribution pattern of cases based on the results of the K-Means Clustering algorithm. The results showed the existence of three main clusters, namely areas with low, medium, and high numbers of cases. Large cities such as Bandung and Bekasi were in the group with the highest number of cases, while peripheral and rural areas showed lower numbers of cases. This finding is expected to be the basis for formulating more effective health policies, especially in education programs, early detection, and community-based interventions to support the goal of eliminating HIV by 2030, then what can be done is to carry out intervention strategies or steps to prevent the spread of HIV tailored to the risk level of each cluster resulting from clustering analysis. Local governments are expected to utilize the results of this mapping to develop more detailed prevention strategies according to the characteristics of each region.

Jurnal Riset InformatikaVol. 7(3)
Mercu Buana University (ID)
Openalex Percentile: Top 93%
Advanced Clustering Algorithms Research
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