Klasterisasi Negara Dunia Berdasarkan Data Sosioekonomi dan Demografi Tahun 2023 dengan PCA dan K-Means - Marpaung, Dhea Romantika; Gunawan, Erin; Fa, Farrel Rio; Christianto, Albert (Program Studi Teknik Informatika - Universitas Komputer Indonesia (UNIKOM), 2025)
The development of social, economic, and demographic factors is an important indicator for assessing the progress of a country. These factors reflect the quality of life, economic conditions, and population dynamics that can influence policies and development planning. Therefore, to better understand a country's conditions, it is important to cluster countries based on similar characteristics in these various aspects. The purpose of this study is to identify clusters of countries worldwide based on the analysis of socio-economic and demographic data for 2023 using Principal Component Analysis (PCA) and K-Means Clustering methods. This analysis examines the relationship between GDP, birth rate, death rate, population, and CO2 emissions. The results reveal three clusters with distinct characteristics. Cluster 0 shows high GDP with low infant mortality and controlled CO2 emissions. Cluster 1 shows lower GDP, high infant mortality, and challenges in the health and economic sectors. Cluster 2, which includes countries like China, India, and the US, has high GDP but faces high CO2 emission issues. These findings indicate the need for integrated policies to improve global well-being by considering economic, health, and environmental factors in a sustainable manner.