Penerapan Principal Component Analysis untuk Menentukan Faktor-Faktor yang Mempengaruhi Kemiskinan di Sumatera Utara - Ameliya Ameliya; Yumna Khairi Amani Piliang; Annisa Hidayah; Eka Sri Hartini Hasibuan (Algoritma : Jurnal Matematika, Ilmu pengetahuan Alam, Kebumian dan Angkasa, 2026)
This study aims to apply the Principal Component Analysis (PCA) method to identify the main factors influencing poverty in North Sumatra Province. Poverty rates in this region show significant variations among districts and cities, influenced by differences in social, economic, educational, and basic facility availability. The data used in this study include eleven indicators related to population, education, health, access to basic services, and economic conditions. All variables were initially normalized to ensure they had comparable scales, then PCA feasibility tests were conducted using MSA, KMO, and Bartlett's test, which indicated that the data were eligible for further analysis. The results of the PCA revealed three main components explaining a total of 69.91 percent of the variation. The first component represents regional population and economic factors, with the largest contributions coming from population density, open unemployment rate, and per capita expenditure. The second component reflects household living conditions, such as access to clean water, adequate sanitation, and health complaints. The third component describes the educational dimension through indicators of the population aged at the primary and secondary school levels. These findings indicate that poverty in North Sumatra is influenced not only by economic factors but also by the quality of basic services and education levels among the population. Therefore, this research is useful for policymakers at the central and regional government levels to consider the factors influencing the increase in poverty in North Sumatra.