Analisis Regresi Bayesian Hurdle Poisson untuk Mengidentifikasi Faktor yang Mempengaruhi Jumlah Kasus Demam Berdarah Dengue (DBD) - Syahfitri, Fatharani; Lubis, Riri Syafitri (Jurnal Pendidikan Matematika : Judika Education, 2024)
This research aims to determine cases of dengue fever using the Bayesian Hurdle Poisson regression method, and the variables that have a significant influence on dengue cases in Medan City in 2022. The method used the Bayesian Hurdle Poisson regression. Research data was analyzed using the SPSS 25 software application and Rstudio 4.4.1 software. Yhe research result show that Bayesian Hurdle Poisson regression in the logit model has the most significant influecne on the number of casses of Dengue Hemorrhagic Fever (DHF) in Medan City in 2022, namely population density (X1), area height (X2), and health facilities (X4). A one unit increase in this variable is equivalent to doubling the number of cases of Dengue Hemorrhagic Fever (DHF) above the initial average, assuming other variables remain constant. Conclusion, Dengue Hemorrhagic Fever (DHF) using Bayesian Hurdle Poisson regression shows yhat the population density variable, the height of area and the number of health facilities play an important in the development of public health in the city of Medan in 2022. Keywords : Dengue Hemorrhagic Fever (DHF), Medan City, Bayesian Hurdle Poisson Regression