<![CDATA[Information technology-based sales applications have emerged as essential solutions for optimizing sales processes, tracking inventory, and understanding customer purchasing patterns. Fokus Computer Store offers a range of products, including computer components, laptops, as well as accessories such as mice, mouse pads, keyboards, USB drives, and other computer components. However, challenges arise in sales efficiency, where certain items tend to accumulate without being sold over extended periods, impacting the store's cash flow. Therefore, an application capable of providing product recommendations based on previous sales data becomes crucial in assisting the store in effective inventory management and maintaining a smooth cash flow. The Apriori method is one form of association rule in the field of data mining. Alongside Apriori, there are other methods within this category, such as Generalized Rule Induction and Hash-Based Algorithms. The Apriori method, being a proven effective algorithm for association analysis, will be employed to uncover potential hidden purchasing patterns within the store's transactional data. By analyzing customer purchase data, this application can identify relationships between frequently co-purchased products. The results of this analysis can be utilized to formulate product recommendations for customers, enhance cross-product sales opportunities, and support inventory management decisions. This application can serve as a point-of-sale system at Fokus Computer Store, with the ability to display the outcomes of the Apriori algorithm calculations based on the input sales data. Despite the application developed by the author having certain limitations, particularly in terms of user interface and data, the author anticipates receiving constructive criticism and suggestions to aid in refining the application for the betterment of its future iterations]]>
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