Pemodelan Indeks Keparahan Kemiskinan di Indonesia Menggunakan Analisis Regresi Robust - Melva Hilda Stephanie Situmorang; Yuliana Susanti (Universitas Sebelas Maret, 2020)
Poverty is one indicator to see the success of development in a country. The Poverty Severity Index can be used as one measure of the magnitude of poverty in an area. In the Poverty Severity Index data in Indonesia, in 2018 there were some outliers, so to analyze it used robust regression. The purpose of this study is to determine the significant factors on the Poverty Severity Index in Indonesia using robust regression with the M-estimation method. The results showed that the Poverty Severity Index model in Indonesia using robust regression was influenced by Gini Ratio, Percentage of Poor Population, and Pure Participation Rate with R-square = 94,8%.Keywords: Poverty Severity Index, robust regression.