Modeling Geographically Weighted Negative Binomial Regression on The Incidence of Adolescent Smoking in Indonesia

This study aims to determine the significant factors affecting adolescent smoking cases in Indonesia with the Geographically Weighted Negative Binomial Regression model. The research method uses a quantitative approach to identify the relationship of each variable and analyze the effect of a treatment. Data analysis was processed using the GWNBR model with the help of R-Studio. The results showed that the case of teenage smoking experienced overdispersion of data with factors that had a significant effect, namely the percentage of poor people, the level of education of parents, the price of cigarettes, the level of income and the percentage of working teenagers, with factors that had a significant effect spatially, namely the percentage of poor people and the percentage of working teenagers. So it can be concluded that the spatial pattern of smoking incidence in Indonesia based on the results of the spatial heterogeneity test shows significant variation across provinces, so that the spatial pattern of the incidence of adolescent smoking is heterogeneous.