Pengelompokan Kabupaten atau Kota di Indonesia Berdasarkan Pelayanan Kesehatan Maternal dengan Algoritma K-Medoids
Abstract
The success of achieving maternal health service programs can be seen from the number of cases of maternal deaths that occur. One of the 3rd target of the SDGs is that by 2030 the number of maternal deaths is expected to be reduced to 70/100,000 live births. In Indonesia, maternal mortality cases in 2020 increased by 430 cases. The purpose of this study is to group districts or cities in Indonesia based on maternal health services with the k-medoids algorithm, where the results of this study can obtain knowledge or information that will assist the government in making strategic policies in the future. The results showed that the optimal number of clusters formed was 2 clusters. Cluster 1 has many as 112 districts or cities that are included in the cluster below the target, and cluster 2 has many as 251 districts or cities that are included in the cluster above the target. The results of the evaluation of the quality of the cluster using the silhouette coefficient from 2 scenarios the k value obtained the best silhouette coefficient average value of 0.46, because the evaluation value is the closest to 1 namely the k = 2
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