Design and Development of a Decision Support System for Determining Production Quantities in the Furniture Industry Using the Tsukamoto Fuzzy Method

Abstract

This study addresses the determination of production quantities in the furniture industry, where inaccurate production planning can result in excess inventory, inefficient resource utilization, or insufficient product availability. The study aimed to design a decision support system for determining production quantities at PT. XYZ using the Fuzzy Tsukamoto method. An empirical system development approach was applied using operational data on demand, production, and inventory obtained from company records for the 2024 period. The model employed three main variables, namely demand, inventory, and production, which were represented through fuzzy sets and processed using fuzzification, IF–THEN rule inference, and weighted-average defuzzification. The current-period data consisted of demand of 65 units and inventory of 55 units. The fuzzification process generated membership degrees of 0.70 and 0.30 for decreasing and increasing demand, respectively, while both low and high inventory had membership degrees of 0.50. The four fuzzy rules produced α-predicate values of 0.50, 0.50, 0.30, and 0.30, with corresponding consequent values of 55, 55, 43, and 43 units. Weighted-average defuzzification generated a mathematical output of 50.50 units, which was adopted as a production recommendation of 50 units for operational implementation. The results indicate that the developed Fuzzy Tsukamoto model can integrate demand and inventory conditions into a structured production quantity recommendation and provide an interpretable basis for production planning at PT. XYZ.