<![CDATA[Café XYZ is a coffee shop that still faces challenges in menu management, such as the absence of a bundling strategy and the limited use of transaction data, which is currently confined to administrative functions. In fact, transaction data has the potential to be utilized in developing more targeted marketing strategies. This final project aims to implement the Apriori algorithm to analyze sales transaction data in order to identify consumer purchasing patterns and recommend appropriate menu bundles. The analysis process follows the CRISP-DM (Cross Industry Standard Process for Data Mining) approach, while the application development adopts the Waterfall method. The result of this project is a web-based dashboard application built using the Flask framework and Python programming language, which can display transaction summaries and product association analysis results in a direct and interactive manner.]]>
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