Implementasi Principal Component Analysis dalam Menganalisis Faktor-Faktor yang Mempengaruhi Indeks Pembangunan Manusia di Provinsi Sumatera Utara

Abstract

This research aims to implement the Principal Component Analysis (PCA) method in analyzing the factors that influence the Human Development Index (HDI) in North Sumatra Province. Principal Component Analysis is a multivariate statistical technique used to reduce the dimensions of data by changing the original variables into a small number of uncorrelated principal components but still retaining most of the information from the original variables. This research uses secondary data obtained from the Central Statistics Agency of North Sumatra Province. The variables analyzed include Average Years of Schooling, Per Capita Expenditure, Life Expectancy, GINI Ratio, Inflation, Population Density, Illiteracy Rate and Expected Years of Schooling. The use of Principal Component Analysis succeeded in reducing the eight variables into two factors, namely the main factor with value. variance of 78.879 and supporting factors with a variance value of 13.484.