Analysis of the Open Unemployment Rate on Poverty in Java in 2024 Using Smoothing Spline Regression

Abstract

Poverty and unemployment are two major issues in economic development that are interrelated and remain a serious concern in Indonesia. Java Island, as the center of economic activity and population in Indonesia, contributes relatively significantly to the national economy, but still faces issues of welfare inequality, including high unemployment rates in several regions and the persistence of people living below the poverty line.  Therefore, analyzing the relationship between the Open Unemployment Rate and the Percentage of the Poor in Java Island is important to understand the socio-economic dynamics that occur. The analysis was carried out using the nonparametric regression method with a smoothing spline estimator. Based on the analysis results, an optimum model was obtained with a value of lambda of 0.04829734. The smoothing spline curve shows a negative relationship pattern, where an increase in the Open Unemployment Rate is followed by a decrease in the percentage of the poor. The Mean Square Error (MSE) value of 11.31277 indicates that the model has a relatively moderate level of prediction error and is able to represent the relationship pattern between variables quite well.