PENGELOMPOKAN PROVINSI DI INDONESIA BERDASARKAN INDIKATOR KESEHATAN LINGKUNGAN MENGGUNAKAN METODE PARTITIONING AROUND MEDOIDS DENGAN VALIDASI INDEKS INTERNAL

Abstract

Environmental health is an important aspect in efforts to achieve public health. The condition of environmental health in Indonesia is varies in each province, so the priorities for increasing environmental health are also different. This study aims to grouping provinces in Indonesia based on environmental health indicators in order to know the high/low environmental quality in each province to assist the government in optimizing environmental health efforts. The grouping of provinces is done partitioning around medoids method which is robust to data containing outliers. The measure of similarity objects is calculated using the Euclidean and Manhattan distances, the selection of the best number of clusters is done by validating the internal index, namely the Calinski-Harabasz index, Baker-Hubert index, silhouette index, C-index, and Davies-Bouldin index. The result of this study is that the best number of clusters are two clusters using the Manhattan distance measurement method, with the largest Calinski-Harabasz index value = 24.10072, the largest Baker-Hubert index = 0.8466251, the largest silhouette index = 0.4246581, the smallest C-index = 0.07290109, and the smallest Davies-Bouldin index = 1.094805.