The Use of the Fuzzy Inference System in Determining the Quality of Goatskin as Raw Material for the Leather Industry

Abstract

Leather products are affected by the quality of the raw hide, the pre-treatment, and the tanning process. Furthermore, some leather products use quality goatskins with the right determination as raw materials. This study aims to determine the quality of goatskin through the use of Fuzzy Logic science. It was conducted using the Sugeno Fuzzy Inference System (FIS), while data analysis was carried out through the Matlab R2018a program. The criteria for using this method were the factors that affected the quality of raw goatskin such as thickness, length of the backline, skin area, number of scratches on the skin, number of holes, presence of boils, lice bumps, and hair loss. The results of the analysis showed that Sugeno FIS could be used to help determine the quality of goatskin with a good accuracy level with a MAPE value of 18%. Furthermore, the FIS method could be used as an appropriate modeling system for determining the quality of goatskin as a raw material for the leather tanning industry.