<![CDATA[Manual transaction management in optical businesses often results in stock data discrepancies, delays in report preparation, and limited marketing reach. This study aims to develop an optical marketplace integrated with a Point of Sales (PoS) system to synchronize transaction and stock data in real-time. In addition, a Content-Based Filtering algorithm is implemented with binary product attribute weighting and customer preference profiles based on transaction frequency, combined with multi-channel Cosine Similarity calculations to generate product recommendations based on product characteristics and customer purchase history. The study was conducted through the stages of needs analysis, system design, implementation, and functional testing using the Black-box Testing method. The results show that the integration of the marketplace and PoS successfully maintains the consistency of transaction and stock data, while the Content-Based Filtering algorithm is able to provide product recommendations that match customer preferences. This study shows that the integration of the marketplace, Point of Sales, and recommendation systems can support the digitalization of optical businesses through more efficient data management and an improved customer shopping experience.]]>
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