Klasterisasi Indikator Kesehatan Ibu dan Anak di Indonesia Menggunakan Hierarchical Clustering Agglomerative - Angelina, Lea; Putri, Dinda Meyda; Ana, Nisfatun Nurul; Syafira, Elsa Izza; Chumairoh, Kamilah Citra; Syaharani, Nabbila Dyah; Fauzi, Fatkhurokhman (Politeknik Statistika STIS, 2025)
Maternal and child health is a top priority in national development, given that high maternal and infant mortality rates remain a significant challenge in Indonesia. Disparities in health indicators between regions indicate that existing inequalities remain insufficiently addressed. This study aims to group 38 provinces in Indonesia based on 14 maternal and child health indicators for 2024 to identify patterns of disparity. The method used is Agglomerative Hierarchical Clustering with multicollinearity tests (VIF) and KMO for data validation. The complete linkage method was selected for its optimal performance, yielding an agglomerative coefficient of 0.742 and the highest silhouette value of 0.2099 at K = 6. The results formed six clusters reflecting similarities in regional characteristics. Several provinces in Papua clustered separately due to their low health indicator achievements. These findings emphasize the need for region-specific intervention policies to address disparities and promote equitable improvements in maternal and child health.