A Comparison Tsukamoto and Mamdani Methods in Fuzzy Inference System for Determining Nutritional Toddlers

A children's nutrition issues still become a nation's problem. Therefore, a nutritional status of children particularly for toddlers needs monitoring and evaluation as periodically, because toddlers will be a children's illustration of health and also both growth and development. One of method, in order to determine a nutritional status of children, has been using an Anthropometry method. The method was must appropriately with international standard measurements which is WHO standard. However, to determine a nutritional status used both explicit and rigid logical, for each small change of value will result from a different category. It is helped by Fuzzy Inference System (FIS) method. Either Fuzzy Tsukamoto or Madani was one of the Decision-Making Method, but they had a different either in Fuzzy Inference System machine or in Defuzzyfication method. Tsukamoto method used MIN implication in inference evaluation machine and Centralized Average method for Defuzzification. Mamdani method used MIN function and rules of composition for MAX function in Inference machine, and composition of the rules with a MAX function in Inference machine and CENTROID method in Defuzzyfication process. The result of measurement presented that Tsukamoto's Fuzzy method gained 82.35% than Mamdani's Fuzzy. The result showed Tsukamoto's fuzzy method more optimum than Mamdani method to determine of Toddlers Nutrition.