Main Article Content
Abstract
In the second half of 2022, the tourism industry started recovering from the vast impacts of the COVID-19 pandemic. Tourism is one of the most feasible sources of income for the small, rural village of Girpasang, situated at the heights of Mount Merapi. Tourist satisfaction has been attributed to the success of tourist destinations and is, therefore, a benchmark for their development. This study aimed to explain the factors that affected tourist satisfaction and other underlying aspects that call for improvement, using confirmatory factor analysis and text mining. The data used was collected from a total of 102 respondents at Girpasang Village within two days. The results showed that there were five common factors affecting tourist satisfaction: staff attitude, reliability of tourist facilities, comfort of tourist facilities, comprehensiveness of facilities provided, and tangible condition of the environment. Based on text mining results of tourist critics, it was found that access roads were the most profound complaint.
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References
UNWTO, Tourism and Rural Development: Understanding Challenges on the Ground – Lessons learned from the Best Tourism Villages by UNWTO Initiative. World Tourism Organization (UNWTO), 2023, doi: 10.18111/9789284424368.
I.G.N.W. Arsana, I.N. Sunarta, and I.N.S. Arida, “Fenomena Pengelolaan Atraksi Wisata Swafoto dan Implikasinya bagi Masyarakat di Desa Wanagiri Kecamatan Sukasada Kabupaten Buleleng,” Jurnal Master Pariwisata (JUMPA), Vol. 5, No. 2, pp. 330–347, Jan. 2019, doi: 10.24843/JUMPA.2018.v05.i02.p07.
A. Parasuraman, L.L. Berry, and V.A. Zeithaml, “Refinement and Reassessment of the SERVQUAL Scale,” Journal of Retailing, Vol. 67, No. 4, pp. 420–450, 1991. [Online]. Available: https://www.proquest.com/scholarly-journals/refinement-reassessment-servqual-scale/docview/228675435/se-2?accountid=62100
T.T. Borishade, O.O. Ogunnaike, O. Salau, B.D. Motilewa, and J.I. Dirisu, “Assessing the Relationship among Service Quality, Student Satisfaction and Loyalty: the Nigerian Higher Education Experience,” Heliyon, Vol. 7, No. 7, pp. 1–8, Jul. 2021, doi: 10.1016/j.heliyon.2021.e07590.
M. Saut and V. Song, “Influences of Airport Service Quality, Satisfaction, and Image on Behavioral Intention towards Destination Visit,” Urban, Planning and Transport Research, Vol. 10, No. 1, pp. 82–109, Dec. 2022, doi: 10.1080/21650020.2022.2054857.
G. Teng, J. Liu, J. Xiao, X. Ma, and Y. He, “Comparative Analysis and Strategy Research of Enterprises Dealing with Network Public Opinion Based on Text Mining,” Procedia Computer Science, Vol. 214, pp. 801–808, 2022, doi: 10.1016/j.procs.2022.11.244.
A. Fauzy, Metode Sampling, 2nd ed. Tangerang, Indonesia: Penerbit Universitas Terbuka, 2019.
I. Kandasamy, W.B.V. Kandasamy, J.M. Obbineni, and F. Smarandache, “Indeterminate Likert Scale: Feedback based on Neutrosophy, Its Distance Measures and Clustering Algorithm,” Soft Computing, Vol. 24, No. 10, pp. 7459–7468, May 2020, doi: 10.1007/s00500-019-04372-x.
P. Leavy, Research Design, 2nd ed. New York, USA: The Guilford Press, 2017.
M. Muhajir, Modul Praktikum Statistika Multivariat Terapan. Yogyakarta, Indonesia: Universitas Islam Indonesia, 2021.
N. Shrestha, “Factor Analysis as a Tool for Survey Analysis,” American Journal of Applied Mathematics and Statistics, Vol. 9, No. 1, pp. 4–11, Jan. 2021, doi: 10.12691/ajams-9-1-2.
D.W. Wichern and R.A. Johnson, Applied Multivariate Statistical Analysis, 6th ed. New Jersey, USA: Pearson Prentice Hall, 2007.
L. Hickman, S. Thapa, L. Tay, M. Cao, and P. Srinivasan, “Text Preprocessing for Text Mining in Organizational Research: Review and Recommendations,” Organizational Research Methods, Vol. 25, No. 1, pp. 114–146, Jan. 2022, doi: 10.1177/1094428120971683.
H. Jung and B.G. Lee, “Research Trends in Text Mining: Semantic Network and Main Path Analysis of Selected Journals,” Expert Systems with Applications, Vol. 162, pp. 1–12, Dec. 2020, doi: 10.1016/j.eswa.2020.113851.
C.-Y. Chu, K. Park, and G.E. Kremer, “A Global Supply Chain Risk Management Framework: An Application of Text-Mining to Identify Region-Specific Supply Chain Risks,” Advanced Engineering Informatics, Vol. 45, pp. 1–17, Aug. 2020, doi: 10.1016/j.aei.2020.101053.