Analisis Kemiskinan di Pulau Jawa Saat Pandemi Covid-19 Tahun 2020 dengan Metode Geographically Weighted Regression (GWR) - Sylvia Agatha Gultom; Agung Priyo Utomo (Politeknik Statistika STIS, 2022)
The Covid-19 pandemic has brought Indonesia's poverty reduction trend to a halt. The implementation of the PSBB policy to prevent the massive spread of the Covid-19 virus turned out to have resulted in an increase in the poverty rate in 2020. As the center of the spread of the virus, the island of Java was most affected. Therefore, this study aims to analyze the conditions of poverty before and during the Covid-19 pandemic and to find out the factors that affect poverty during the Covid-19 pandemic on the island of Java. The dependent variable used is the percentage of poor people, while the independent variables are economic growth, TPT, HDI, and the percentage of informal workers. The analysis was carried out using the Geographically Weighted Regression (GWR) method. The results of the analysis show that before the pandemic, the majority of Java Island had moderate poverty status, but in 2020 the majority were in high status. From the test results obtained that the GWR model is better than the RLB model. The partial test of local coefficients shows that economic growth has a positive and negative effect, TPT and the percentage of informal workers have a positive effect, while HDI has a negative effect on poverty.