<![CDATA[The rapid expansion of technology has profoundly reshaped the commercial sector, shifting conventional trading activities toward web-based e-commerce platforms due to their superior efficiency, practicality, and accessibility. Although numerous digital marketplaces exist, several vendors still lack built-in product customization. A product recommendation system plays a critical role, as the absence of personalized features may impair the quality of the user experience and eventually lead to lower platform engagement. This study aims to build an e-commerce platform integrated with the Content Based Filtering algorithm, which provides tailored item suggestions matching distinct user preferences. The system engineering process follows the structured phases of the Waterfall model, incorporating requirement analysis, architectural design, implementation, software testing, and system maintenance. Finally, the validation framework relies on Blackbox Testing to verify execution accuracy alongside the System Usability Scale (SUS) method to assess the metrics of user satisfaction and interface friendliness.]]>
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