ANALISIS REGRESI SPASIAL DURBIN UNTUK MENGANALISIS FAKTOR-FAKTOR YANG BERHUBUNGAN DENGAN PERSENTASE PENDUDUK MISKIN - Yulita Putri Lokang; Ignatius Aris Dwiatmoko (Jurnal Ilmiah Matrik, 2019)
The percentage of poor people is the percentage of the population who have a monthly per capita expenditure below the poverty line. In this study, spatial Durbin regression used to know the factors which is giving effect to the percentage of poor population with maximum likelihood method to estimate parameters. This method used because it can maximize the probability of occurrence of each parameter. From 6 independent variables that are thought to be related to the percentage of poor people, there are only 4 independent variables that can be modeled by the spatial Durbin regression model because of the presence of significant spatial autocorrelation based on the Moran Index test. That are school participation rates aged 16-18 years, inflation, life expectancy at birth, and the human development index. The measure of the goodness of the Durbin spatial regression model calculated by looking for the value of R2 is 68,4%