<![CDATA[The utilization of the internet in the tourism is very helpful for tourists in planning trips, including in exploring local tourist areas. The existence of special media such as smart tourism web facilities to publish local tourist attractions and tourist facilities in the local area certainly help stakeholders and tourists. To facilitate the tourists as web users to access information about visited area, it is necessary to have a recommendation system that can provide a recommendation regarding the tourist needs such as tourist destinations, lodging, restaurants and even souvenir shops typical of the local area. Recommendation system development can be done through two basic methods, namely: Content Based Recommendation and Collaborative Filtering. This study aims to show how to implement content-based filtering in providing content-based recommendations on supporting the development of smart tourism webby utilizing cosine similarity and K-Nearest Neighbor. This study shows that Content Based Recommendation can provide recommendation according to the tourist needs based on the content that has been selected by other users.]]>
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