Pannee Suanpang, Pathanapong Pothipasa
This paper aims to develop Artificial Intelligence (AI) recommended agrotourism supporting community-based tourism in the post-COVID 19 periods for a new dimension of the next normal case study in Sisaket Province of Thailand. The proposed system was developed under Software Development Life Cycle (SDLC) to provide an impressive experience, and new model that respect to the needs of tourists in agrotourism. In this research, a decision support system was developed and provided tourism information through a mobile application to t collect traveler’s information such as gender, age, number of days travelled, budget and preferred travel style. The information was submitted to classification to generate the appropriate tourism programs using the Extreme Learning Machine. After the classification process, an appropriate itinerary will be created and sent to the tourists back. In additional, the proposed system also provides a feedback and rating section to assess the correspondence of the tour arrangement with the high level of traveler’s satisfaction. To evaluate the proposed system, 400 test data from 400 tourists was tested. The experimental results show that, the tourist satisfaction was highest, with quick process, convenient, the system is easy to use and the system is clear and beautiful respectively. Moreover, an AI recommended agrotourism will be used to support and promote community-based tourism in a pilot filed in Sisaket Province, of Thailand to boosting travel industry in the Post Period of COVID-19 to obtain a new approach of the next normal travel.