Analisis Kualitas Modal Manusia Tingkat Provinsi di Indonesia Menggunakan K-Means Clustering dan Regresi Logistik Biner - Aurellia, Nur Aisya; Sari, Riska Meyliana; Muzakki, Naufal Fadli (Seminar Nasional Official Statistics, 2025)
The Human Capital Index (HCI) is one of the indicators used in human development evaluations, with the aim of improving the welfare and advancement of human resources in various sectors of life. Limitations in provincial-level HCI data, as well as limitations in the data of HCI components, hinder the HCI calculation process. Therefore, an alternative approach was applied to assess human capital quality by examining components such as life expectancy, average years of schooling, and stunting prevalence using K-Means cluster analysis. The results indicate that provinces in Indonesia form two clusters: the low HCI group and the high HCI group. This study aims to examine the influence of several variables on HCI categories using binary logistic regression analysis. The results show that per capita GDP, internet penetration rates, and rice productivity have a significant positive impact on human capital quality in Indonesia.