PEMANFAATAN ALGORITMA APRIORI UNTUK EFISIENSI STOK BAHAN BAKU PADA BISNIS KATERING (STUDI KASUS: DESI CAKE'N COOKIES)

Suboptimal management of raw material stocks can lead to excess or shortage of supplies, thereby hindering smooth production. This study aims to develop a raw material stock requirement prediction system using the Apriori algorithm to support decision-making at Dewi Cake'n Cookies catering business. The research data was taken from records of 20 cake product sales transactions, which were analysed to find patterns of interrelationships between raw materials that are often used together. The minimum support parameter was set at 50% and the minimum confidence at 80% to produce relevant association rules. The implementation results show that the system is capable of predicting raw material combinations with a certainty level of up to 100%, thereby assisting in efficient and data-driven raw material procurement planning. These findings prove that the application of the Apriori algorithm can be an effective solution for inventory management in small and medium-sized businesses.