<![CDATA[This study aims to analyze raw material inventory control using the Material Requirements Planning method as raw material inventory control and to forecast inventory in 2024. The data analysis method is qualitative quantitative descriptive analysis. This analysis was carried out at CV Kopi Citarasa Persada. Efficiency data processing uses Minitab 21 and Excel. The problem in this study is related to frequent running out of raw materials due to late ordering by the company. The results of the study show that the availability of raw materials for coffee beans, packaging and stickers has a Lead Time of 4 days with the application of the Lot Sizing method, Part Period Balancing technique and the Wagner Within Algorithm which are the most efficient in obtaining minimum ordering costs in this study. Robusta ground coffee demand data for a year in 2023 produces forecast data for January and February 2024 by comparing the Moving Average and Single Exponential Smoothing techniques. The comparison results show that the Moving Average technique is suitable for forecasting raw material inventory because it has a smaller MAD value, the smaller the forecast value obtained, the more accurate it is in determining the size of the data as it was originally. Keywords: Forecasting, Lot Sizing, Material Requirements Planning.]]>
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