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All Journal Enthusiastic : International Journal of Applied Statistics and Data Science Jurnal Sintak
Kariyam
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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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.
Cluster Analysis and Discriminant Analysis for Grouping Provinces Based on Factors Affecting Poverty Levels in Indonesia 2018-2020 Kariyam; V.R, Baiq Jasmin Sabhira Safwa; Alifia, Juan Latif; Oktarani, Larasati; Andanitya, Putri Pratista; Ikhsani, Willia Diva
JURNAL SINTAK Vol. 4 No. 2 (2026): MARET 2026
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/jsintak.v4i2.802

Abstract

Poverty is a condition that occurs due to the inability of a person or group to meet the minimum basic needs, such as food, clothing, health, housing, and education, which are necessary to maintain survival. The poverty level of an area is influenced by various factors, including the Open Unemployment Rate (TPT), the Provincial Minimum Wage (UMP), and the Human Development Index (IPM). This research aims to group provinces in Indonesia based on factors that affect poverty and determine the discriminatory function of the group formed. The analysis method used is cluster analysis to group provinces into several poverty level groups and discriminatory analysis to form a separating function between the groups. The results of cluster analysis show the formation of three groups, namely the group with the highest poverty level consisting of 7 provinces, the group with moderate poverty level consisting of 8 provinces, and the group with the lowest poverty level which includes other provinces. Furthermore, discriminant analysis produces a discriminant function that is able to distinguish between poverty levels quite well. The results of this research are expected to be considered by the government in formulating poverty alleviation policies that are more on target
Co-Authors Alifia, Juan Latif Andanitya, Putri Pratista Hafis Muhammad Nizam Ikhsani, Willia Diva Nova, Rahma Fatwa Nur Aulia Maknunah Oktarani, Larasati Rizky Mardhatillah Tasya Apriliana V.R, Baiq Jasmin Sabhira Safwa