Abstract:
Relationship analysis on spatial data can be done by using the method Geographically
Weighted Poisson Regression (GWPR), which is a local form of Poisson regression which is
applied to spatial data, where location is considered. The purpose of this study was to
determine the GWPR model and the factors that influence the number of cases of Dengue
Hemorrhagic Fever (DHF) in Indonesia in 2015. The spatial weighting used is the Gaussian
kernel function and the optimum bandwidth. The parameter estimation method for the GWPR
model is Maximum Likelihood Estimate (MLE). The results of this study indicate that the
maximum likelihood estimator is obtained using the Newton-Raphson iteration method and
the factors that affect the number of DHF cases in Indonesia are local. Locally influencing
factors are population density, number of health workers, number of health facilities, and
amount of rainfall.
