Abstract
The Merah Putih Village Cooperative plays an important role in strengthening the local economy, yet sales in Silian Satu Village are still conducted conventionally. This study designs and develops an e-commerce website with a product recommendation system based on Content-Based Filtering to help customers discover products through content similarity. The study uses the Research and Development (R&D) method with the Waterfall model. The system is built with PHP and MySQL using a client–server architecture. Term weighting applies TF-IDF, while similarity is measured with Cosine Similarity based on product names, categories, and tags. Black Box Testing of 27 scenarios showed that all passed. However, this testing does not establish recommendation relevance, as metrics such as Precision@K, Recall@K, and Mean Average Precision (MAP) have not been evaluated. Thus, the system is functional, but recommendation accuracy still requires further evaluation.
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