Clustering of Provinces in Indonesia Based on Environmental Health Indicators Using K-Medoids

According to the Ministry of Health of the Republic of Indonesia, key environmental health indicators include access to safe drinking water, adequate sanitation, and healthy living environments. As of 2023, only 10.21% of Indonesian households had access to safe sanitation, far from the government’s 2045 target of 70%. Indonesia’s ranking at 164th out of 180 countries in the 2022 environment performance index (EPI), with a score of 28.20 out of 100, further underscores the need for targeted interventions. This study aims to classify Indonesian provinces based on environmental health indicators, thereby supporting more effective policy prioritization. The k-medoids clustering algorithm was employed due to its robustness to outliers and flexibility in handling mixed data types, making it well-suited for this context. This study utilized data from 34 provinces in 2023, sourced from the Ministry of Health. These provinces were grouped into two clusters, with cluster 2 representing provinces with stronger environmental health performance. The clustering results were validated using the silhouette coefficient, confirming the quality of the groupings. Provinces in cluster 1 require greater policy attention to improve environmental health conditions. This study demonstrates the potential of robust medoids-based clustering for guiding targeted environmental health strategies in developing countries.

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Publication Details

Journal
Enthusiastic International Journal of Applied Statistics and Data Science
Published
2025-04-26
DOI
https://doi.org/10.20885/enthusiastic.vol5.iss1.art9
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
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article

Clustering of Provinces in Indonesia Based on Environmental Health Indicators Using K-Medoids

Edy Widodo, Widya Saputri Agustin, Safwah Ayu Mardiyyah, Qolbiyatus Syifa Az Zahra et al.
Enthusiastic International Journal of Applied Statistics and Data Science
Data Mining and Machine Learning Applications
article

Clustering of Provinces in Indonesia Based on Environmental Health Indicators Using K-Medoids

Edy Widodo, Widya Saputri Agustin, Safwah Ayu Mardiyyah, Qolbiyatus Syifa Az Zahra, Anggun Nur Anggreany
article en

Abstract

According to the Ministry of Health of the Republic of Indonesia, key environmental health indicators include access to safe drinking water, adequate sanitation, and healthy living environments. As of 2023, only 10.21% of Indonesian households had access to safe sanitation, far from the government’s 2045 target of 70%. Indonesia’s ranking at 164th out of 180 countries in the 2022 environment performance index (EPI), with a score of 28.20 out of 100, further underscores the need for targeted interventions. This study aims to classify Indonesian provinces based on environmental health indicators, thereby supporting more effective policy prioritization. The k-medoids clustering algorithm was employed due to its robustness to outliers and flexibility in handling mixed data types, making it well-suited for this context. This study utilized data from 34 provinces in 2023, sourced from the Ministry of Health. These provinces were grouped into two clusters, with cluster 2 representing provinces with stronger environmental health performance. The clustering results were validated using the silhouette coefficient, confirming the quality of the groupings. Provinces in cluster 1 require greater policy attention to improve environmental health conditions. This study demonstrates the potential of robust medoids-based clustering for guiding targeted environmental health strategies in developing countries.

Enthusiastic International Journal of Applied Statistics and Data Science
Islamic University of Indonesia (ID)
Openalex Percentile: Top 64%
Data Mining and Machine Learning Applications
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