Developing Chatbot System to Promote Bio-Tourism Crane Wetlands, Thai Species, Mueang District, Buriram Province

Authors

  • Kamolrat Somchai Department of Information Technology, Faculty of Science, Buriram Rajabhat University
  • Sangdaow Noppitak Department of Information Technology, Faculty of Science, Buriram Rajabhat University
  • Warinpiphat Watcharapongkasem Department of Information Technology, Faculty of Science, Buriram Rajabhat University
  • Purim Chadaratanathiti Department of Information Technology, Faculty of Science, Buriram Rajabhat University

Keywords:

biotourism, intelligent response system, Wetland Area of Thai Cranes

Abstract

Ecotourism in the Thai Sarus Crane Wetland, Buriram Province, has gained increasing popularity; however, effective information dissemination channels remain limited. This study aimed to: (1) assess the ecotourism potential of the Thai Sarus Crane Wetland in Mueang District, Buriram Province; (2) develop an intelligent chatbot system to promote ecotourism in the area; and (3) transfer the developed system to local stakeholders. Three groups of participants were involved. Fifteen key informants were selected through purposive sampling for in-depth interviews to assess ecotourism potential. Five experts were selected via purposive sampling to evaluate the system’s efficiency. Additionally, thirty-six users were selected through simple random sampling to assess user satisfaction. The research instruments included structured interview forms, the developed intelligent chatbot system, an efficiency evaluation form, and a user satisfaction questionnaire. Qualitative data were analyzed using content analysis, while quantitative data were analyzed using descriptive statistics, including mean and standard deviation. The findings revealed that the Thai Sarus Crane Wetland demonstrates strong ecotourism potential across multiple dimensions, including attraction value, tourism activities, local products, service quality, and community participation. The intelligent chatbot system was developed using Artificial Intelligence (AI) and Natural Language Processing: NLP technologies and deployed on the LINE platform. The system effectively delivered ecotourism-related information to users. Overall user satisfaction was high (x̄=4.48 SD=0.49), indicating positive acceptance of the system.

References

BEDO. (2021). BEDO launches bio-tourism, creating value and income for local communities [In Thai]. Bangkok Business News.

Bilabdulla, K. (2021). Chatbot application for interrogation tasks: Case study of Betong Police Station Facebook Page [In Thai] [Master’s thesis, Prince of Songkla University]. Prince of Songkla University

Biodiversity-Based Economy Development Office. (2022). Bio-tourism handbook [In Thai]. Public Organization.

Chan, P. (2021). Intelligent chatbot system for academic counseling: A case study of faculties at Sripatum University [In Thai] [Research report]. Sripatum University.

Chowdhary, G. G. (2020). Natural language processing: Fundamentals, methods and applications. Elsevier.

Dech-oom, P., & Rattanasuwongchai, N. (2019). Biodiversity-based tourism standards handbook [In Thai]. Kasetsart University.

Expedia Group. (2018). TAT and Expedia Group partner to promote tourism to Thailand’s secondary cities [In Thai]. https://www.tatnews.org/2018/09/tourism-authority-of-thailand-and-expedia-group-announce-a-memorandum-of-understanding/

Joobanjong, W., Sanchana, W., Mulom, R., & Suesatsakulchai, A. (2021). Tourism promotion in Tak province using virtual reality technology [In Thai]. Journal of Information Science and Technology, 11(1), 56–64. https://doi.org/10.14456/jist.2021.7

Jueng, E., Janruang, J., Phobphimai, S., & T. Siriwattana, S. (2023). The development of digital platform for local tourism support: Case study of Sikhoraphum District Surin Province [In Thai]. EAU Heritage Journal Science and Technology, 17(3), 193–206. https://he01.tci-thaijo.org/index.php/EAUHJSci/article/view/264551

Jurafsky, D., & Martin, J. H. (2023). Speech and language processing (3rd ed.). Pearson.

Kla-asa, P., & Buachum, S. (2015). Tourism patterns from data sharing on social media websites using data mining techniques: A case study of Chai Nat Province [In Thai] [Research report]. Chandrakasem Rajabhat University.

Maisak, R., & Kaewjinda, J. (2019). Chatbot application for promoting agro-cultural tourism [In Thai] [Research report]. Rajamangala University of Technology Phra Nakhon.

Nithiyuwith, T., Treenuntharath, T., & Kumtapol, Y. (2024). The development of semantic virtual reality media for promoting health tourism in Khaokho District, Phetchabun Province [In Thai]. EAU Heritage Journal Science and Technology, 18(1), 90–106. https://he01.tci-thaijo.org/index.php/EAUHJSci/article/view/262266

Oracle Corporation & Parkers, C. (2016). Can virtual experiences replace reality?. Oracle Corporation.

Rohman, M. A., & Subarkah, P. (2024). Design and build chatbot application for tourism object information in Bengkulu City. TECHNOVATE: Journal of Information Technology and Strategic Innovation Management, 1(1), 28-34. https://doi.org/10.52432/technovate.1.1.2024.28-34

Rothjanawan, K., Rattanachu, C., & Phetjirachotkul, W. (2024). Tour guide application for tourist via line chatbot - in the case of multicultural tourism, Narathiwat province [In Thai]. International Journal of Science and Innovative Technology (IJSIT), 7(1), 35–43. https://ph01.tci-thaijo.org/index.php/IJSIT/article/view/255134/171905

Royal Forest Department. (2022). Wetland management and conservation handbook [In Thai]. Ministry of Natural Resources and Environment.

Siharad, D., & Sookprasert, A. (2024). Improving performance of using machine learning techniques and application for perceiving tourists’ hotel staying behaviors [In Thai]. EAU Heritage Journal Science and Technology, 18(1), 161–175. https://he01.tci-thaijo.org/index.php/EAUHJSci/article/view/264174

Suwanna, A., & Thientitrap, P. (2018). Community-based conservation of Eastern Sarus Cranes for wetland ecotourism at Huai Jorakae Mak Reservoir Non-hunting Area, Muang District, Buri Ram Province [In Thai]. Journal for Community Development and Life Quality, 3(1), 17–28. https://so02.tci-thaijo.org/index.php/JCDLQ/article/view/132630

Zoological Park Organization. (2022). Thai crane conservation and breeding project [In Thai]. Zoological Park Organization of Thailand.

Downloads

Published

2026-04-21

How to Cite

Somchai, K., Noppitak, S., Watcharapongkasem, W., & Chadaratanathiti, P. (2026). Developing Chatbot System to Promote Bio-Tourism Crane Wetlands, Thai Species, Mueang District, Buriram Province. EAU Heritage Journal Science and Technology (online), 20(1), 206–220. retrieved from https://he01.tci-thaijo.org/index.php/EAUHJSci/article/view/282993

Issue

Section

Research Articles