Evaluasi Faktor Sosial dan Kemiskinan di Provinsi Papua: Pendekatan Analisis Komponen Utama

Abstract

This study analyzes the poverty rate in Papua Province through a multivariate statistical approach using Principal Component Analysis (PCA). Papua faces complex challenges in the form of high poverty, social inequality, and low Human Development Index (HDI), exacerbated by difficult-to-access geography and limited infrastructure. Using secondary data from the Papua Province Central Statistics Agency, this study identified six main variables: the number of health workers, the number of poor people, the labor force participation rate, the percentage of households without sanitation facilities, the implicit price index of GRDP, and HDI. The results of the analysis show that these variables form two main factors: Demographic & Social and Human Resources, which collectively explain 75.44% of the data variability. The Demographic & Social factor covers access to facilities and social conditions of the community, while the Human Resources factor focuses on the quality of human resources in the region. However, although these two factors are significant, the model is considered less than optimal in summarizing all related variables. This study suggests the use of a lower significance level to strengthen the model and the development of more targeted government programs to overcome poverty in Papua. The PCA method used provides a focused picture to support more effective data-based policy making. Thus, this study contributes to mapping crucial factors to support sustainable development in Papua.