This research is a descriptive research. The object of this research is Sebellas Apparel which has a dependent inventory model. The purpose of this study is to analyze Material Requirement Planning (MRP) which begins with analyzing the master production schedule, product structure, list of material requirements, which then ends with determining the most optimal lot sizing. The product analyzed is a Jersey Bola product that has the highest number of requests. Sources of data used in this study are primary and secondary data. Data analysis method used is demand forecasting with time series method, Material Requirement Planning (MRP), and optimal lot size determination with Lot for Lot (LFL), Part Period Balancing (PPB), and Economic Order Quantity (EOQ) techniques using help of POM for Windows 3 software. In determining the optimal lot size, lot sizing techniques that produce optimal lot sizes for Dri-Fit Fabrics, Poliflek, Obras Yarns and Plastics are Lot for Lot (LFL) and Part Period Balancing (PPB) techniques because these two techniques have a total cost the same and the smallest of the three techniques used. In this situation, one lot sizing technique can be selected. However, in this study for the Dri-Fit Fabric the technique chosen was Lot for Lot (LFL) because this technique considered minimization of the cost of storage, the amount ordered was the same as the amount needed. Whereas for Poliflek, Obras Yarns, and Plastik used Part Period Balancing (PPB) technique because because this technique takes into account the quantity of purchases that can balance the ordering costs and storage costs based on cumulative net needs of several periods combined. Lot sizing technique for Sewing Thread uses Part Period Balancing (PPB) technique because it has a smaller total cost than the three techniques used. Whereas for the Labels of these three techniques can be used all, but in this study the technique used is the Economic Order Quantity (EOQ) technique because with this technique the company can have a safety stock so as not to run out of raw materials.