Analisis Faktor yang Mempengaruhi Kemiskinan Provinsi Jawa Timur Tahun 2023 dengan Metode Principal Component Analysis - Bintang Amirul Mukminin; Muhammad Hasan Alwi Abu Sifa; Sri Pingit Wulandari (Asosiasi Riset Teknik Elektro dan Informatika Indonesia, 2024)
Poverty is one of the main issues in Indonesia although many policies have been implemented by the government to overcome this problem. With this problem, a study was conducted which aims to identify factors that affect poverty in East Java in 2023 using the principal component analysis (PCA) method. PCA is a multivariate analysis technique used to extract information from correlated data, so as to summarize several variables into principal components. In this study, the variables used include the number of poor people, percentage of poor people, poverty severity index, open unemployment rate, labor force participation rate, and life expectancy from 38 districts/cities in East Java. It was found that the data characteristics had low variance with the exception of one variable, and met the assumptions of multivariate normal distribution, interrelationship between variables, data sufficiency, and correlation between variables suitable for PCA. Factor analysis with PCA produces two main components, namely community living conditions and labor conditions, which can represent the original variables in their influence on poverty in East Java. Suggestions from this study are expected to be a reference for policy makers in improving community welfare and labor conditions in East Java. Future research is expected to add related variables to obtain more detailed results.