Spatial Modeling of Infant Mortality Rate In South Central Timor Regency Using GWLR Method With Adaptive Bisquare Kernel And Gaussian Kernel - Teguh Prawono Sabat (Humanistic Network for Science and Techno lo gy, 2017)
Geographica lly Weighted Logistic Regression (GWLR) was regression model consider the spatial fac tor, which could be used to analyze the IMR. The number of Infant Mortality as big as 100 cases in 20 15 or 12 per l000 live birth in South Central Timor Regency. The aim of this study was to determine the best modeling of GWLR with fixed weighting function and Adaptive Gaussian Kernel in the case of infant mortality in South Central Timor District in 20 15. The response variable (Y) in this study was a case of infant mortality , while variable predictor was the percentage of neonatal first visit (KN I) (X I), the percentage of neonatal visit 3 times (Complete KN) (X2), the percentage of pregnant get Fe tablet (X3), percentage of poor fami lies pre prosperous (X4). This was a non-reactive study, which is a measurement which individuals surveyed did not realize that they are part of a study, wi th analysis unit in 32 sub-districts of South Central Timor Di stricts. Data ana lysis used open source program that was Excel, R program, Quantum GIS and GWR4. The best GWLR spatial modeling wi th Adaptive Gaussian Kernel weighting function , a global model parameters GWLR AdaptiveGaus ·ian Kernel weighting fu nction obtained by g (x) = 0.941086 - 0,892506X4, GWLR local models with adaptive Kernel bisquare weighting function in the 13 Districts were obtained g(x) = /Jo - {J0X4 , factors that affect the cases of infant mortality in 13 sub-di tricts of Sou th Central Timor Regency in 2015 was the percentage of poor famil ies pre prosperous.