<![CDATA[Segmented strategies are needed to improve the quality of public health. K-Means and K-Medoids clustering analysis could be applied to determine the distribution of public health indexes and to classify them by regencies/cities in Nusa Tenggara Timur province. This research conducted clustering analysis based on several public health indexes, namely Percentage of Women Aged 15-49 Years Who Have Given Birth in Last 2 Years with Medical Personnel Assistance, Percentage of Population Aged 0-59 Months by Complete Immunization, Percentage of Women Who Have Given Birth in the Last 2 Years by Normal Body Weight of Live Birth, Percentage of Households with Access to Sanitation, Percentage of Households with Access to Proper Drinking Water, and Percentage of Population Who Did not Smoke Tobacco in the Last Month. Based on Davies-Bouldin Index (DBI), it is known that K-Means is better than K-medoids Clustering. The First cluster of regencies/cities have best indicators, namely Timor Tengah Utara, Belu, Lembata, Flores Timur, Sikka, Ende, Ngada, Manggarai, Manggarai Barat, Malaka, Nagekeo, and Kupang City. The second cluster consists of Sumba Barat, Sumba Timur, and Sumba Tengah, have fairly good health indicators, but sanitation conditions need to be improved. The third cluster have fairly good health condition but government needs to pay attention about immunization in Alor, Kupang, Rote Ndao, Sumba Barat Daya, and Manggarai Timur. The fourth cluster, Timor Tengah Selatan and Sabu Raijua have low percentage of proper sanitation and complete immunization. Based on this, segmented health-related policies by public health current condition could be assigned.]]>
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