Muslihah, Ririn Ridania2021-10-192021-10-192021-03wahyu sari yenihttps://repository.unri.ac.id/handle/123456789/10259This paper discusses about rice production modeling in Indonesia with Mixed Geographically Weighted Regression (MGWR) approach. The MGWR model is a combination of multiple linear regression models and Geographically Weighted Regression (GWR), which model variables that are global and local. The estimated parameters of the MGWR model are obtained using the Weighted Least Square (WLS) method. The optimum bandwidth is selected by using the Cross Validation (CV) method. Rice production in Indonesia is influenced by factors such as harvest area, rainfall, fertilizer, and farmers. MGWR model produces variables of local nature is the area of harvest, while the variables that are global are rainfall, fertilizer and farmers. MGWR model is a best model used to model rice production data in Indonesia based on Akaike Information Criteria Corrected valueenRice productionMixed Geographically Weighted RegressionWeighted Least SquareCross ValidationAkaike Information Criterion CorrectedArticle