Pembuatan E-Commerce Berbasis Website Dengan Sistem Rekomendasi Content-Based Filtering

E-commerce has grown rapidly, providing convenience for consumers to shop online. However, with its growth, many users face difficulties in finding products that match their needs and preferences amidst a vast array of options. One solution to this problem is the implementation of recommendation systems that help users quickly and efficiently discover relevant products. This study aims to build an e-commerce website for Herva ID, a local fashion company specializing in women's apparel, by implementing a recommendation system using the Content-Based Filtering method. This method allows for more personalized and relevant product recommendations for each user by analyzing product attributes that users have previously viewed or purchased.
Using Content-Based Filtering in the early stages of development proves to be more efficient compared to other methods, such as Collaborative Filtering or Hybrid Filtering, which require greater complexity. The recommendation system can help customers find products that match their style and preferences, while also improving operational efficiency and increasing sales for Herva ID. With the e-commerce application equipped with a recommendation system, Herva ID can enhance the customer shopping experience and strengthen customer relationships, ultimately supporting business growth. Overall, the implementation of a Content-Based Filtering recommendation system can be an effective strategic step in the development of e-commerce within the local fashion sector.