Creating a Program to Predict the Clothing Size Using Fuzzy Logic

This study presents a program to predict trousers’ size using a fuzzy logic technique. There are three variables to input into the program to give the output result of the fit size. The first variable is the waist measurement. The second variable is the hip measurement. The third variable is the trousers’ length measurement. The size determination is done by the Min-Max rule through the IF-THEN structure, effectively managing the commands in the model. The fuzzy rule matrix consists of 108 rows and 6 columns, in which each row represents a fuzzy rule. Each row is a fuzzy rule. The first column represents six groups of neck circumference. The second column represents six groups of hip circumference. The third column represents three groups of pants length. The fourth column represents six predicted output sizes. The fifth column is the weight coefficient. The last column represents the type of logical connection. This size prediction method only takes about five to six seconds to predict the fit size. This reduces the time to choose the size compared to the traditional method. In addition, it reduces the risk of damaging the sample. This method to predict sizes can apply to many other types of clothing as well as many other fields of the garment industry