The Integration of Kansei Engineering and Kano Model on Natural Language Processing (NLP) to Support Development of Service Product in the Borobudur Temple Tourism

A novel integration of Natural Language Processing (NLP), Kansei Engineering, and the Kano model identified critical service quality attributes to enhance visitor satisfaction at Borobudur Temple Compounds. Analyzing TripAdvisor data, researchers extracted key sentiments such as 'exit,' 'morning,' 'temple,' 'sunrise,' and 'heat,' alongside unlisted but necessary factors like ticket pricing, elephant enclosure management, and pamphlets. The study revealed two primary areas for improvement: the distance between facilities and the management of the elephant cage, both deemed unenjoyable by visitors. This approach offers a data-driven strategy to optimize tourism services at this UNESCO World Heritage Site, balancing visitor expectations with operational efficiency.

Azzam, A., Jati, N. P., & Maghfiroh, M. (2024). The Integration of Kansei Engineering and Kano Model on Natural Language Processing (NLP) to Support Development of Service Product in the Borobudur Temple Tourism. International Journal on Advanced Science, Engineering and Information Technology, 14(2), 600–607. https://doi.org/10.18517/ijaseit.14.2.19290