This research aims to provide solutions to managers of the tourist attraction in increasing the number of tourist visits in the form of a marketing model that is cheap, easy, right on target, and can reach all elements of society without time and place limits, namely by using a social media platform. With this model, it is hoped that it can be used by the management and can further increase the number of tourist visits to Alas Kedaton. This tourist attraction has experienced problems in terms of the number of tourist visits since the Covid 19 pandemic. Until now the number of tourist visits has not returned to normal. On normal days it is still around 150 tourists, but it can increase to 800 people during the Galungan holidays. Even though the price of admission is 15,000 for children and 20,000 for adults, while foreign tourists are 30,000/person, with a low number of tourist visits, managers will still have difficulty covering their operational costs. The tourist attraction is located at Kukuh village, Marga sub-district, Tabanan district is a nature tour managed by the local village community so it is also a mainstay for villagers who work in this tourist attraction. Some of them work in the managerial field and some are souvenir traders who also serve as guides at the tourist attraction. Souvenir sellers at these attractions are also given the opportunity to become local tour guides at these attractions without asking for payment, but at the same time, they can offer their wares to the tourists they guide. While the tourism products offered by the Alas Kedaton tourist attraction are closely related to the preservation of nature and animals. This is perfect for educational tours. That way the market for this tourist attraction is actually very broad, especially for school children, students, teachers, lecturers, and other environmental observer communities. To create a social media platform-based marketing model, primary and secondary data will be sought. Primary data was obtained by conducting interviews with the object manager and secondary data was obtained from offline and online library sources. The data was then reduced, described, categorized and concluded, and analyzed using a qualitative descriptive analysis technique.