Pengelompokan Provinsi Berdasarkan Capaian Indikator Kesehatan Lingkungan di Indonesia Tahun 2020

Authors

  • Maysarah Sabariah Kudadiri Institut Pertanian Bogor
  • Pika Silvianti Department of Statistics, IPB University
  • Farit Mochamad Afendi Department of Statistics, IPB University, Indonesia

DOI:

https://doi.org/10.29244/xplore.v11i3.879

Keywords:

cluster analysis, kmeans, standard deviation ratio

Abstract

Environmental health is part of public health in general. If each province is associated with the achievement of environmental health indicators, the achievements will not be the same. The grouping of provinces will make it easier for the government to determine priorities for environmental health development in Indonesia. The grouping of provinces in this study used cluster analysis. The method used is the k-means because it has the smallest standard deviation ratio compared to other cluster analysis methods. The grouping results obtained are four clusters. The first cluster consists of one province that has the characteristics of high Percentage of Medical Waste (PMW) indicator achievement and the lowest percentage of villages with open defecation stops indicator achievement. The second cluster consists of six provinces that have the highest achievement of the SBS indicator and the lowest achievement of the PMW indicator. The third cluster consists of 20 provinces that have the characteristics of achieving high percentage of public places and facilities that are supervised indicators and the smallest achievement of PMW indicators. The fourth cluster consists of seven provinces that have the characteristics of high achievement of the percentage of drinking water facilities supervised/checked for drinking water quality and the lowest achievement of the PMW indicator.

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Published

2022-09-30

How to Cite

Kudadiri, M. S., Silvianti, P., & Afendi, F. M. (2022). Pengelompokan Provinsi Berdasarkan Capaian Indikator Kesehatan Lingkungan di Indonesia Tahun 2020. Xplore: Journal of Statistics, 11(3), 191–202. https://doi.org/10.29244/xplore.v11i3.879

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