A Fuzzy Logic Approach to Measure Underweight Among Kindergarten’s Kids (Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis, 2018)
Nowadays, being underweight during childhood is equally risky as being overweight. Underweight children lead to decrement in their academic performance, a social problem as well as challenging attitudes. Underweight people are likely to be less fit and active, which would also increase their cardiovascular risk and health problem. Their mind also becomes inflexible while their concentration and ability to decide are markedly weak. The purpose of this study is to evaluate the chances of having underweight among the children by using Fuzzy Logic Approach. Besides that, the comparison of effectiveness result of underweight between Body Mass Index (BMI) method and Fuzzy Logic Approach using the Mamdani method will be made. The data on weight and height of the children were collected from 3 kindergartens in Perlis. The result shows that 60 to 70 percent of children having an underweight in the range between 79.1% to 91.2% compare to the BMI method that is only 10 percent of children have underweight. It shows that Mamdani method was very effective compared to BMI Method because of the flexibility from the output control that is a smooth control function despite a wide range of input.