KLASTERING KOTA DAN KABUPATEN DI INDONESIA BERDASARKAN UMUR HARAPAN HIDUP SAAT LAHIR DENGAN K-MEDOIDS
Keywords:
cluster, K Medoids, life expectancy, HDIAbstract
One of the uses of cluster analysis is to predict the state of objects, and in this study, 514 provinces in Indonesia are grouped into four clusters based on LifeExpectancy at birth. The historical data used is sourced from BPS for a period of 11 years, from 2010 to 2019. The purpose of this provincial grouping is to provide input to local governments and policy makers regarding provincial clusters in their area. With the hope of making improvements or increasing efforts to increase life expectancy at birth and reduce mortality at birth. The algorithm used is K-Medoids which can perform clusters with the advantage of being able to overcome noise and oulier in large data. The results obtained are Cluster 1 as many as 125 provinces, Cluster 2 as many as 119 provinces, Cluster 3 as many as 137 provinces and Cluster 4 as many as 133 provinces. Life expectancy is one of the components in calculating the Human Development Index.
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