Analysis of Factors Affecting the Amount of Waste Generation in East Java Province Using the Random Forest Regression Method

Abstract

The issue of waste generation in East Java Province continues to rise in line with population growth and economic activities. This study aims to analyze socioeconomic factors influencing waste generation in 2024 using the Random Forest Regression (RFR) method. The dataset consists of secondary data from SIPSN and BPS, covering 38 districts and cities with five predictor variables: land area, population growth, population density, average expenditure per capita, and GRDP. The optimal model parameters were obtained at mtry = 2 and ntree = 500. The results indicate that GRDP and land area are the most influential factors based on the feature importance analysis. An R² value of 0.198 suggests that other unobserved variables also contribute to variations in waste generation. This study is expected to provide data-driven insights for local governments in formulating more effective and sustainable waste management policies.