<![CDATA[This research discusses the implementation of the Content-Based Filtering method in a cat food recommendation system. The problem in this research is motivated by the difficulty of cat owners and pet shops in determining appropriate food, because there are many variations of products that differ in cat age, type of food, brand, price, composition, nutritional content, and product characteristics. This research was conducted to create a recommendation system that can help users in determining the appropriate cat food choice, by looking at product characteristics and specific needs of cats. This research utilizes the Content-Based Filtering method to analyze and recommend products, through the stages of data collection, data preprocessing, attribute weighting using Term Frequency-Inverse Document Frequency, and similarity calculation using Cosine Similarity. The research data was obtained through observation, interviews, literature study, and documentation of cat food products. The results show that the system built can help users determine cat food based on the suitability between user criteria, cat needs, and product characteristics. This system can also facilitate users in obtaining information and appropriate cat food choices. Based on this, the Content-Based Filtering method is considered effective to be applied in a recommendation system, to assist the cat food selection process in a more structured and efficient manner.]]>
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