Spatial durbin model to identify influential factors of diarrhea

Problem statement: An analysis of regression modeling which influenced by the characteristics of the region is very important. That modeling is the spatial autoregressive model. One type of spatial autoregressive model is a Spatial Durbin Model (SDM), which performs a lag effect of the dependent and independent variables. This model was developed because the dependencies in the spatial relationships doesn't only occur in the dependent variable, but also on the independent variables. Modeling of diarrhea and the factors that influence is the case that followed this method. Approach: This problem was solved by identification of spatial autocorrelation and modeling to get the influence factors of diarrhea. The modelings were Ordinary Least Square (OLS) and SDM. Then, it was compared between two models. This research located in Tuban Regency, East Java, Indonesia. Results: There were a spatial autocorrelation on diarrhea and the factors variable that influence it. Furthermore, the SDM was giving better performance than OLS model. The results of SDM showed that the lag in the dependent and independent variables significantly affected. These independent variables were source of drinking water, health center and medical personnel which were significant at α = 5%. Conclusion: SDM has good performance to identify influential factors of diarrhea which has spatial factors.