heresultsissuedbythemethodthatweproposewiththemedicaldoctor’sassessmentbasedonthedegreeofsimilarity to his opinion. Performing the comparison of the data related to the field of health research is also carried out by Castanho et al20 to predicting pathological stage of prostate cancer and Kelecs et al21 for diagnosis breast cancer. With 311 numbers ofrelevant data we find that the resultsthathave been launched bythe architecture of fuzzymodel that we propose is 87.46% equal to medical doctor’s statement which also uses the data from the laboratory related to whether someone has no potential against DM or someone has the potential against DM. However, there is 12.54% difference between our results with the medical doctor’s statement. If there is a real data shown that someone got a positive with DM but the there is no potential against the age, our architectural of fuzzy model will conclude that it is only potential against DM not high potential against DM. The matching process is done between our final result with HbA1c examination which acts as the real data are used by medical doctors as a source. In this paper we use Matlab as software to perform computation of fuzzy hierarchical model with centroid as defuzzification technique.