METODE PRINCIPAL COMPONENT ANALYSIS PADA FAKTOR-FAKTOR YANG MEMPENGARUHI KEMISKINAN PULAU SUMATERA

Abstract

Sumatera Island is the sixth largest island in the world, located in Indonesia, consisting of 154 regencies/cities. Sumatra Island is ranked fourth in the Indonesia for having the highest percentage of poor people, with 5,8 million in 2020. The factors that influence poverty can be viewed from the fields of population, employment, health, education, and the economy. The number of these factors can be reduced by using one of the methods in multivariate analysis, namely Principal Component Analysis (PCA). PCA aims to reduce data consisting of many variables that are interrelated with one another but still maintain the largest possible variance from the original data. The variables used to consist of 7 variables, namely, Open Unemployment Rate (𝑋1), Average Length of Schooling (𝑋2), Expenditure Per Capita (𝑋3), Population Density(𝑋4), Total Population (𝑋5), Gross Regional Domestic Product (𝑋6), and Life Expectancy(𝑋7). By using the correlation matrix in PCA analysis, three principal components are obtained with a cumulative proportion of variance of 77,8% in explaining the diversity of the original variable.