PERAN PARIWISATA RELIGI DAN BUDAYA DALAM PERMINTAAN WISATA CIREBON

Authors

  • Ahmad Ghazy Dananjaya Institut Teknologi Bandung

Keywords:

religious tourism, culture, travel demand, cirebon, sustainability

Abstract

Cirebon, as a region rich in cultural and religious heritage, holds great potential as a prime tourist destination. This study aims to identify the role of religious and cultural tourism in boosting travel demand in Cirebon. Utilizing visitor data analysis and online news discourse through Structural Topic Modeling (STM) and SARIMAX methods, the research explores the relationship between media coverage, promotional strategies, and tourism trends. Findings reveal that cultural events such as the Muludan Festival and religious pilgrimages to Sunan Gunung Jati's tomb are key attractions. Digital promotions through social media and the involvement of human and virtual influencers enhance Cirebon's exposure as a travel destination. However, sustainability challenges, including overtourism and waste management, must be addressed to maintain tourist experience quality. This study provides strategic recommendations, including data-driven and technological management, to foster sustainable tourism development in Cirebon.

Downloads

References

Alaei, A. R., Becken, S., & Stantic, B. (2019). Sentiment Analysis in Tourism: Capitalizing on Big Data. In Journal of Travel Research (Vol. 58, Issue 2, pp. 175–191). SAGE Publications Ltd. https://doi.org/10.1177/0047287517747753

Bulchand-Gidumal, J., William Secin, E., O’Connor, P., & Buhalis, D. (2024). Artificial intelligence’s impact on hospitality and tourism marketing: exploring key themes and addressing challenges. Current Issues in Tourism, 27(14), 2345–2362. https://doi.org/10.1080/13683500.2023.2229480

Centobelli, P., & Ndou, V. (2019). Managing customer knowledge through the use of big data analytics in tourism research. Current Issues in Tourism, 22(15), 1862–1882. https://doi.org/10.1080/13683500.2018.1564739

Chon, K. K. S., & Hao, F. (2024). Technological evolution in tourism: a Horizon 2050 perspective. Tourism Review. https://doi.org/10.1108/TR-10-2023-0753

Correia, A., & Kozak, M. (2022). Past, present and future: trends in tourism research. Current Issues in Tourism, 25(6), 995–1010. https://doi.org/10.1080/13683500.2021.1918069

De Luca, G., & Rosciano, M. (2024). Google Trends data and transfer function models to predict tourism demand in Italy. Journal of Tourism Futures. https://doi.org/10.1108/JTF-01-2023-0018

Dolores Ordóñez, M., Gómez, A., Ruiz, M., Ortells, J. M., Niemi-Hugaerts, H., Juiz, C., Jara, A., & Butler, T. A. (n.d.-a). 8 IoT Technologies and Applications in Tourism and Travel Industries.

Dolores Ordóñez, M., Gómez, A., Ruiz, M., Ortells, J. M., Niemi-Hugaerts, H., Juiz, C., Jara, A., & Butler, T. A. (n.d.-b). 8 IoT Technologies and Applications in Tourism and Travel Industries.

Dwivedi, Y. K., Pandey, N., Currie, W., & Micu, A. (2024). Leveraging ChatGPT and other generative artificial intelligence (AI)-based applications in the hospitality and tourism industry: practices, challenges and research agenda. International Journal of Contemporary Hospitality Management, 36(1), 1–12. https://doi.org/10.1108/IJCHM-05-2023-0686

Ghesh, N., Alexander, M., & Davis, A. (2024). The artificial intelligence-enabled customer experience in tourism: a systematic literature review. In Tourism Review (Vol. 79, Issue 5, pp. 1017–1037). Emerald Publishing. https://doi.org/10.1108/TR-04-2023-0255

Gursoy, D., Malodia, S., & Dhir, A. (2022). The metaverse in the hospitality and tourism industry: An overview of current trends and future research directions. Journal of Hospitality Marketing and Management, 31(5), 527–534. https://doi.org/10.1080/19368623.2022.2072504

Hariri, R. H., Fredericks, E. M., & Bowers, K. M. (2019). Uncertainty in big data analytics: survey, opportunities, and challenges. Journal of Big Data, 6(1). https://doi.org/10.1186/s40537-019-0206-3

Iorio, C., Pandolfo, G., D’Ambrosio, A., & Siciliano, R. (2020). Mining big data in tourism. Quality and Quantity, 54(5–6), 1655–1669. https://doi.org/10.1007/s11135-019-00927-0

Jabeen, F., Al Zaidi, S., & Al Dhaheri, M. H. (2022). Automation and artificial intelligence in hospitality and tourism. Tourism Review, 77(4), 1043–1061. https://doi.org/10.1108/TR-09-2019-0360

Karali, A., Das, S., & Roy, H. (2024). Forty years of the rural tourism research: reviewing the trend, pattern and future agenda. Tourism Recreation Research, 49(1), 173–200. https://doi.org/10.1080/02508281.2021.1961065

Li, J., Xu, L., Tang, L., Wang, S., & Li, L. (2018). Big data in tourism research: A literature review. Tourism Management, 68, 301–323. https://doi.org/10.1016/j.tourman.2018.03.009

Song, H., & Liu, H. (2017). Predicting Tourist Demand Using Big Data. In Tourism on the Verge: Vol. Part F1056 (pp. 13–29). Springer Nature. https://doi.org/10.1007/978-3-319-44263-1_2

Song, H., Qiu, R. T. R., & Park, J. (2023). Progress in tourism demand research: Theory and empirics. In Tourism Management (Vol. 94). Elsevier Ltd. https://doi.org/10.1016/j.tourman.2022.104655

Tussyadiah, I. (2020). A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism. Annals of Tourism Research, 81. https://doi.org/10.1016/j.annals.2020.102883

Wu, X. X., Shi, J., & Xiong, H. (2024). Tourism forecasting research: a bibliometric visualization review (1999–2022). Tourism Review, 79(2), 465–486. https://doi.org/10.1108/TR-03-2023-0169

Downloads

Published

2025-03-04

How to Cite

Dananjaya, A. G. (2025). PERAN PARIWISATA RELIGI DAN BUDAYA DALAM PERMINTAAN WISATA CIREBON. PARIWISATA BUDAYA: JURNAL ILMIAH PARIWISATA AGAMA DAN BUDAYA, 10(1), 53–65. Retrieved from https://ojs.uhnsugriwa.ac.id/index.php/parbud/article/view/4489
Abstract viewed = 40 times