Riry Sriningsih, Mohammad Soleh, Reni Prima Gusty, Helma, Yusmet Rizal
Poisson regression (PR) is a method commonly used to analyze count data that is assumed to be equidispersed. However, in reality overdispersion often occurs, so PR is not suitable for modeling such data because the model produced biased parameter estimates. One method to overcome overdispersion is generalized Poisson regression (GPR). In addition, the GPR model is further developed into a geographically weighted generalized Poisson regression (GWGPR) model that considers spatial effects. The purpose of this study is to determine the GWGPR model of the number of dengue cases in Java and the factors that affect the number of dengue hemorrhagic fever (DHF) cases in Java. Spatial weights were calculated using an adaptive bi-square kernel weighting function, and the optimal bandwidth was determined using cross-validation (CV) criteria. The results obtained are the factors affecting the number of DHF cases in Java Island. © 2026 Author(s).
Department of Mathematics, Universitas Negeri Padang, Padang, Indonesia; Department of Mathematics, Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia; Medical-Surgical Nursing, Universitas Andalas, Padang, Indonesia
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