KLASIFIKASI TINGKAT PENGANGGURAN TERBUKA DI PULAU JAWA MENGGUNAKAN REGRESI LOGISTIK ORDINAL

Abstract

Unemployment is one of the indicators for measuring the economic conditions of a region. It is also a social and economic problem in many countries, including Indonesia, especially in areas with a density of economic activity, such as Java Island. The purpose of this study was to classify and analyze the factors that affect the open unemployment rate in cities and regions on Java Island, which are categorized as low, medium, and high. The research method used in this study was ordinal logistic regression analysis. The data source comes from the BPS website in 2023 with four predictor variables: population size, labor force participation rate, average years of schooling, and gross regional domestic product at constant prices. The research results show that the variables population size and labor force participation rate had a significant effect on the open unemployment rate, while the variables average years of schooling and gross regional domestic product at constant prices did not have a significant effect on the open unemployment rate with the accuracy of the ordinal logistic model is 77.27%.

Keywords

• regresi logistik ordinal
• tingkat pengangguran terbuka
• ordinal logistic regression, open unemployment rate