IMPLEMENTASI MERN STACK PADA INVENTORI MENEJEMEN SISTEM DI TOKO ARABIC PARFUME BANDAR LAMPUNG

Abstract

The Arabic Perfume store in Bandar Lampung faces challenges in inventory management due to manual record-keeping, which is prone to errors, resulting in either stock shortages or overstocking. Survey results indicated that 70% of perfume stores experienced difficulty tracking Inventory, 55% struggle to update stock data in real-time, and 50% are vulnerable to human error. These issues hindered operational efficiency. This study aimed to design and implement an inventory management system based on the MERN Stack (MongoDB, Express.js, React.js, and Node.js), integrated with the Apriori algorithm to analyse customer transaction patterns. The system supported real-time stock monitoring, generated association rules to assist in procurement planning, and featured a responsive and user-friendly interface. The implementation results demonstrated improved stock record accuracy and facilitated procurement decision-making. Recommendations for future development included adding machine learning-based demand forecasting features, automated minimum stock level notifications, mobile application. development, integration with Point of Sale (POS) systems, and customer satisfaction analysis modules. The system also showed potential for expansion to support centralized inventory management across multiple branches, thereby enhancing overall efficiency.