<![CDATA[Food is a fundamental human need that plays a crucial role in supporting health. For housewives, cooking is a daily routine in preparing nutritious meals for their families. In the digital era, technology simplifies recipe searching, but the abundance of available recipes often makes it difficult for users to find ones that match their available ingredients. To address this issue, this study develops a recipe recommendation system based on content-based filtering. The dataset was collected from cookpad.com and includes recipe names, ingredients, cooking duration, and cooking instructions. The system is designed using a content-based filtering approach and cosine similarity to measure the relevance between user input and existing recipe data. Users simply input ingredients, seasonings, or types of dishes they have, and the system provides relevant recommendations. Testing results show that the system can accurately identify and recommend recipes based on keywords, including specific cases such as "Soto Ayam Bening." The recommendations generated are reasonably accurate and assist users in selecting the most suitable recipes according to their needs. This system is expected to offer a practical solution for users in determining appropriate meal choices based on the ingredients available at home]]>
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