Modeling Human Development Index in Papua and West Sumatera with Multivariate Adaptive Regression Spline

Abstract

The Human Development Index (HDI), which is an indicator as a comprehensive description of the measure of achievment development in the quality of human life in a region. In Indonesia, there are still many areas with low HDI, especially in Papua Province. This study aims to model and find out what factors affect HDI in Papua Province and West Sumatera Province, using Multivariate Adaptive Regression Spline (MARS). MARS is a modeling methods that can handle high-dimensional data, namely data that has independent variables and a sampel size of data with unknown data patterns in advance, and can be applied to see interaction between the variables used. The result of this study obtained that the best MARS model for Papua Province is a combination of BF=24, MI=2, and MO=0 with GCV=0.55953. while the best MARS model for West Sumatera Province ia a combination of BF=24, Mi=2, and MO=0 with GCV=0.02697. the factors that significantly affect HDI in Papua Province and West Sumatera Province are average lenght of schooling (X2), adjusted per-capita income (X6), life expectancy (X1), percentage of poor population (X4), anf gross regional domestic product (X3). The level of importance of each variable for Papua Province is 100%, 45.26%, 29.24%, 6.55%, and 6.27%. while for West Sumatera Province it is 100%, 96.73%, 57.54%, 34.13%, and 29.6%,respectively. So that in this case based on research results the average lenght schooling (X2) is the variable that most influences HDI in the two regions.