This research aims to implement the Naïve Bayes method in determining restocking decisions for Ffactory2nd, a fashion product retail business entity. Ffactory2nd has a crucial need to effectively manage its inventory and make informed decisions regarding restocking. Sales data were collected from August to December 2023, with testing conducted on 16 selected products as samples. The analysis results indicate that the system can provide accurate restocking recommendations based on inventory levels. The Naïve Bayes method is employed for classifying restocking into two categories: Restock (Yes) and No Restock. The analysis demonstrates that the system is capable of delivering accurate restocking recommendations, aiding inventory managers in more effective decision-making. Alpha and beta functional testing indicates that the restocking determination system has been successfully implemented and well-received by users. User satisfaction reached an average level of 93%, indicating a positive impact of the system on inventory management at Ffactory2nd.
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