Sistem Rekomendasi Pemilihan Produk Skincare

The skin is the largest organ of the body that requires proper care to maintain a healthy body. Along with the increasing trend of skincare or skincare in Indonesia, many consumers face difficulties in choosing products that suit their skin type and problems. In this case, the Content-Based Filtering-based recommendation system can provide a solution for users to choose skincare products that suit their preferences based on existing product reviews. This study aims to develop a skincare product selection recommendation system using the Content-Based Filtering approach, which is based on product description analysis and user reviews. The novelty of this study lies in the use of TF-IDF weighting and Cosine Similarity calculation to analyze similarities between products based on user descriptions and reviews. The research method used is qualitative with a descriptive approach, which involves data collection through scrapping from the Female Daily platform and data analysis using pre-processing and TF-IDF weighting techniques. The results of the study show that this recommendation system can provide the most relevant skincare products based on the similarity of reviews and product descriptions, thus helping users choose products that suit their skin needs. This study concludes that Content-Based Filtering is effective in helping users find the right skincare products, minimizing product selection errors, and improving user experience.