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Analyzing Tourist Satisfaction Using Factor Analysis and Text Mining: An Ecotourism Study in Girpasang Village Kariyam; Tasya Apriliana; Nur Aulia Maknunah; Hafis Muhammad Nizam; Rizky Mardhatillah; Nova, Rahma Fatwa
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 4 Issue 1, April 2024
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol4.iss1.art4

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.