Blood sugar levels of diabetes mellitus patients modeling with Bayesian mixture model averaging

Diabetes Mellitus (DM) is one of the most dangerous diseases to humans because of the effects of complications caused. According to WHO, in 2013, the total number of DM patients in Indonesia was ranked 7^th in the world and this disease was ranked 6^th in the world as the leading causes of human death. Bayesian Mixture Model Averaging (BMMA) is a Bayesian approach for multiple mixture models with the model parameter estimation using the averaging rule. The purpose of this study would be built the BMMA models to blood sugar levels of Diabetes Mellitus (DM) patients through simulation studies where the simulation data built on cases of blood sugar levels ofDMpatients inRSUDSaifulAnwar Malang. The results of this study have succed to built the BMMA normal models with 2 components mixture that could accommodate the real condition of theDMdata with driven data concept.