The Borobudur Temple Compounds is one of the spearheads of Indonesian tourism, anticipating introduction to the international community. Currently, the management of the compound is focused on maintaining the existing condition of tourism and increasing enthusiasm among visitors to experience the temple area. Amidst the challenges posed by the COVID-19 pandemic, the management has implemented stringent health procedures to ensure the safety and health of visitors. Therefore, this study aimed to investigate the service required to increase visitor enthusiasm and satisfaction in the Borobudur Temple Compounds using the Natural Language Processing (NLP) method to extract visitor sentiments as Kansei words from TripAdvisor. The results obtained were processed using Kansei Engineering type 1 to determine the most critical service quality category through Kano model. The integration of NLP, Kansei Engineering, and Kano model proved effective, showing attributes like popular Tripadvisor searches, such as exit, morning, temple, sunrise, and heat. Other attributes not listed but considered necessary based on Kansei Engineering and Kano model integration were identified, such as ticket prices, elephant enclosure management, and pamphlets. Based on the results, it was discovered that the management of Borobudur Temple Compounds needed to improve in two main aspects. These included the distance between each facility and the compound elephant cage, considered unenjoyable.