Khomaria Nurul Ainy
1. Department of Statistics, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia; 2.Center for Data and Information Technology, Ministry of Education, Culture, Research and Technology of the Republic

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Profiling the Inequality of School Water, Sanitation, and Hygiene Facilities Among Indonesian Regions Using Cluster Analysis Didik Bani Unggul; Khomaria Nurul Ainy; Roudlotul Jannah
JURNAL KESEHATAN LINGKUNGAN Vol. 15 No. 1 (2023): JURNAL KESEHATAN LINGKUNGAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jkl.v15i1.2023.27-36

Abstract

Introduction: Humans rely heavily on Water, Sanitation, and Hygiene (WASH) facilities. Goal 6 of the Sustainable Development Goals (SDGs) emphasizes ensuring communities possess universal access to clean water and sanitation. Because WASH is tremendously crucial in schools, the objective of this study is to provide a comprehensive profile of regional inequalities based on the availability of WASH indicators through cluster analysis. Methods: This study administered cross-sectional data from 514 regencies/cities in Indonesia with three variables, i.e. percentage of access to water, sanitation, and hygiene at public and private elementary schools. The profiling was performed by conducting K-means clustering method. Results and Discussion: Public and private schools were examined separately as the p-value in the difference test was less than 0.05. In accordance with the silhouette plot, the optimal number of clusters was two for each category. For the public-school category, the number of regencies/cities in Cluster 1 was 380 regencies/cities and 134 regencies/cities were in Cluster 2. For the private school category, Cluster 1 incorporated 418 regencies/cities and Cluster 2 merely encompassed 96 regencies/cities. Conclusion: Two clusters for each type of school had been established with Cluster 1 consisting of areas with high availability of WASH facilities while areas in Cluster 2 possessed a relatively low percentage in the three WASH indicators. There were 66 regencies/cities, generally located in eastern Indonesian provinces, grouped in Cluster 2 for both types of schools.