<![CDATA[Overstock and delays in fulfilling requests for spare parts at Hyundai Nagoya can occur due to ineffective stock management. The objective of this research is to develop a web-based platform warehousing system that increases the efficiency of goods rotation using the First In First Out (FIFO) method. In addition, the Random Forest algorithm is used to categorize components according to goods movement patterns. The movement patterns of goods are divided into three categories: fast moving, medium moving and slow moving categories. The data analysed includes order history, frequency of use, and stock of goods for the last six months. By implementing a web-based system, real-time stock monitoring and order recommendations based on historical demand patterns can be made. The study's findings demonstrate that the FIFO approach effectively lowers the chance of old products piling up, increasing recording accuracy, and speeding up spare parts distribution. With a classification model accuracy of 75%, this method can improve warehouse management and help make more accurate decisions. In conclusion, the FIFO method can be used in a web-based warehousing system to optimize spare parts stock management at Hyundai Nagoya. Keywords: FIFO, Hyundai Nagoya, Random Forest, Stock Management, Warehousing System]]>
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