<![CDATA[PT. XYZ is a manufacturing company that produces various products such as PVC pipes, concrete products, and wooden furniture, including chairs. Currently, the company faces constraints in controlling raw material inventory for BR-600 Chair and Folding Chair products because it has not used scientific calculation methods in planning its needs. This causes an imbalance between the amount of inventory and production needs, which has an impact on overstock and understock. Overstock results in increased storage costs and the risk of obsolete raw materials, while understock causes production delays and potential loss of sales. This study aims to design a raw material inventory control system using a dynamic deterministic approach and determine the most optimal method. The approaches used include demand forecasting using the Single Exponential Smoothing and Moving Average methods, as well as calculating safety stock, optimal order size (lot size), and total inventory costs. Furthermore, inventory control planning is carried out using the Wagner-Whitin Algorithm and Silver-Meal Algorithm. The results of the study show that the application of the Wagner-Whitin Algorithm and Silver-Meal Algorithm methods in dynamic deterministic inventory control can reduce the total cost of raw material inventory for BR-600 Chair and Folding Chair by 5% and 3% respectively compared to the company's real method previously used by the company. Between the two, the Wagner-Whitin Algorithm method proved to be the most optimal with a total inventory cost of IDR 3,388,833,000.]]>
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