<![CDATA[This research aims to optimize the inventory management of animal food stocks at Endman Petshop by implementing Mamdani fuzzy logic. In recent years, the petshop industry has experienced rapid growth, making inventory stock management increasingly important to efficiently meet customer demands. The input variables used in this study include Sold Goods, Demand, Price per Item, and Profit, while the output variable is Stock. Sales data from the top five products at Endman Petshop over the course of a year serve as the basis for developing the Mamdani fuzzy logic model. By implementing the Mamdani fuzzy logic method using MATLAB software, the research results demonstrate that the application of Mamdani fuzzy logic can help optimize animal food stock inventory. Considering the fluctuating variability of demand, price, and profit, this model assists Endman Petshop in making more accurate decisions in stock inventory management. This research contributes significantly to enhancing operational efficiency and profitability for Endman Petshop, offering practical solutions to address challenges in increasingly complex inventory management. As part of a continuously evolving industry, this research becomes a relevant reference for petshop practitioners and business owners in optimizing stock inventory and better meeting customer demands. The research findings indicate a significant improvement in operational efficiency and profitability for Endman Petshop. The results show that the implementation of the Mamdani fuzzy logic method can reduce inefficient stock inventory]]>
