<![CDATA[Culinary businesses in Indonesia, such as Brownies Cinta Karanganyar, face challenges in helping consumers choose products with the best taste. This study aims to implement a Brownies Cinta menu recommendation system using the Content-Based Filtering method with the cosine similarity algorithm. The system was developed through the SDLC Waterfall stages: planning, design, implementation, testing, and maintenance. The TF-IDF algorithm is used to calculate the initial value, which is then processed with cosine similarity to produce accurate recommendations. The test results show that the "Lapis Kukus Fruity (Regular)" and "Brownies Oven Almond (Regular)" menus have the highest cosine similarity values, reaching 0.950. In contrast, the D19 document with the lowest cosine similarity value is considered irrelevant. In conclusion, the developed content-based recommendation system can provide the best and most relevant recommendations to users. The use of the TF-IDF and cosine similarity algorithms has proven to be accurate, increasing consumer satisfaction in choosing products. This system helps Brownies Cinta consumers determine the products they want to buy, facilitating the menu selection process.]]>
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