Pemodelan Data Kemiskinan di Pulau Sumatera dengan Regresi Multilevel Spline Linear Truncated - Davala, Muhammad Ridzky; Annisa, Nurul Mutiara; Siswanto, Siswanto; Kalondeng, Anisa (Universitas Sebelas Maret, 2024)
Poverty is one of the world's biggest challenges that is still a problem, both in developing and developed countries, including Indonesia. Around 27.5 million people live below the national poverty line in Indonesia. Because it is the largest archipelago, poverty problems in each region also vary, including on the Sumatra Island. One of the efforts to alleviate poverty can be done through identifying factors that affect the percentage of poor population using truncated linear spline multilevel regression model. Multilevel modeling is a statistical approach specifically used to analyze data with a two-level structure. This approach allows an understanding of the contribution of individual and group-level factors to the response variable. The predictor variables considered are per capita expenditure, open unemployment rate, and human development index at the district/city level (level-1), as well as population growth rate and economic growth rate at the provincial level (level-2). The results of this study show that the best multilevel regression model at level-1 uses three knot points, while at level-2 it uses two knot points. The factors that affect PPM in Sumatra Island in 2021 at level-1 are per capita expenditure and at level-2 are population growth rate and economic growth rate. The factors that affect percentage of poor population in Sumatra Island in 2021 are expected to provide a more in-depth view of the socio-economic conditions on the island of Sumatra.