Wonosobo Regency is one of the places with great potential for tourism if only it optimise visitor understand like this be a perfect place to keep developing. There are many tourists who come to Floral City every year. The absence of proper in-context tourism information systems here only makes it harder for tourists to get the right kind of (contextualized) data that suits their needs. Several efforts have been made to improve the previous result by developing tourism recommendation systems through the application of an Item-based Collaborative Filtering algorithm; this research tries to address that matter. We decided on this algorithm, which can be recommended based on the similarity between travel sights. Thus, recommendations are in compliance with the user’s choice. In testing the effectiveness of Cosine Similarity in calculating similarity values between each tourist attraction, a Case study was conducted on various tourism objects in Wonosobo R D. The results indicated that the Item-based Collaborative Filtering algorithm can be successfully used to construct personalized recommendations that are both precise and relevant for tourists. Accordingly, the resulting recommendation system is hoped to help get tourism information quickly and increase tourist visits to Wonosobo. In addition, this study also helps popularize relatively less well-known tourist destinations, which could have a good effect on the development of locals and attract visitors to improve tourism service quality. The performance of the system, assessed using Root Mean Square Error and Mean Absolute Error metrics, supports that recommendations are very pertinent.