Limited storage capacity and fluctuations in the number of orders require effective reorder management at CV. Yos Salim. This research aims to develop a decision support system for recommending the appropriate quantity of goods to be ordered using the *Fuzzy Inference System with the Tsukamoto method*. The research utilizes historical data on demand and inventory for 20 types of goods during the period from January to December 2025, with demand and inventory serving as input variables and the order quantity serving as the output variable. The system development method used is the *Waterfall* method, which consists of requirements analysis, system design, implementation, and system testing. Meanwhile, the decision-making process is carried out using the *Fuzzy Tsukamoto* method through the stages of fuzzification, rule base formation, inference, and defuzzification. The results show that the developed system is capable of generating recommendations for the quantity of goods to be ordered based on the conditions of demand and available inventory. The testing results indicate that the system achieved a success rate of 100%, based on 14 testing scenarios consisting of 10 *Black Box Testing* scenarios and 4 *White Box Testing* paths, with all scenarios obtaining a Valid status. *Black Box Testing* demonstrated that all system functions operated according to user requirements, while *White Box Testing* showed that the program logic operated in accordance with the designed and implemented algorithm. Based on these results, it can be concluded that the *Fuzzy Tsukamoto* method can be applied to assist decision-making in controlling the quantity of goods ordered in a more objective, consistent, and effective manner.