While the GWNBR method obtained two groups of districts/cities based on significant variables. For negative binomial regression, two variables have a significant effect on DHF cases.
The results of research with poisson regression obtained three variables that have a significant effect on dengue cases. GWNBR is better at modeling the number of DHF cases because it has the smallest AIC value than poisson regression and negative binomial regression. GWNBR modeling uses a fixed exponential kernel for weighting function.
Meanwhile to see the spatial effect, we can use the Geographically Weighted Negative Binomial Regression (GWNBR) method. If in poisson regression there is overdispersion, it can be overcome using negative binomial regression. Characteristics of data the DHF cases is count data, so this research is carried out using poisson regression. Regarding the less handling of DHF spread, it is necessary to make a plan by identify the factors that allegedly affect that case. The number sufferers of this disease is still high because the mortality rate is still above the national target. Dengue Hemorrhagic Fever (DHF) is one of the diseases with unsual occurrence in Central Java and spread throughout the regency/city.
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