<![CDATA[This study aims to apply the Autoregressive Integrated Moving Average (ARIMA) method to forecast the inventory of pearl accessories at CV Aonine Pearls. The ARIMA method has proven effective for short-term forecasting and can assist the company in determining optimal stock levels, thereby reducing the risk of overstock or understock situations. The implementation of ARIMA is expected to improve operational efficiency, reduce storage costs, and enhance customer satisfaction through timely and adequate product availability. This abstract summarizes the research objective, methodology used, and expected outcomes. It briefly explains the use of ARIMA for stock prediction and its benefits in optimizing inventory management. The forecasting model shows consistent stock movement stability across products. The applied ARIMA model achieved an accuracy rate of 86.20% based on validation using historical data, providing a reliable empirical foundation for inventory optimization and production strategy planning for Q1 2024.]]>
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