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All Journal Jurnal Pilar Nusa Mandiri Jurnal Statistika dan Aplikasinya Enthusiastic : International Journal of Applied Statistics and Data Science
Qori'atunnadyah, Marita
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics Social Sciences Other

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Mapping Domestic and Foreign Tourists in East Java Using C-Means Clustering Qori'atunnadyah, Marita
Jurnal Statistika dan Aplikasinya Vol. 8 No. 1 (2024): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.08105

Abstract

Tourism is a priority sector identified by the government for its potential to drive economic growth, job creation, community development, and regional progress. Although significant, it still requires a detailed mapping of tourist visit patterns to optimize regional tourism potential. This study uses the C-Means Clustering method to categorize districts and cities in East Java based on the number of domestic tourists and foreign tourists. Data from 2018 to 2022 is used to identify different patterns and groups. The methodology involves clustering the data based on similarities in the number of visitors, which provides insight into regional tourism dynamics. The results revealed three main groups of domestic tourists: high, medium, and low-visitation regions. For foreign tourists, five groups were identified, reflecting variations in the level of tourist visits. These groups help understand the distribution and concentration of tourists in different regions, which is important for targeted promotion strategies and efficient resource allocation. A limitation of this study is that it does not go deeper into external factors affecting tourism, such as the COVID-19 pandemic. The originality of this research lies in the application of the C-Means Clustering method to map domestic tourists and foreign tourists in East Java not simultaneously, thus providing valuable insights for policymakers and industry stakeholders to encourage collaboration and innovation in the tourism sector.
MAPPING OF DOMESTIC AND FOREIGN TOURIST VISITS IN EAST JAVA USING THE DBSCAN METHOD Qori'atunnadyah, Marita
Jurnal Pilar Nusa Mandiri Vol. 21 No. 1 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i1.6073

Abstract

Tourism is important in economic growth and regional development, especially in East Java Province with diverse tourist attractions. However, the mapping of domestic and foreign tourist visit patterns in this province is still limited. For this reason, this study uses the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method which can group density-based data without determining the number of clusters from the beginning and handle noise. The study aims to map districts/cities in East Java based on the number of tourist visits from 2018 to 2022, using visit data from the East Java Provincial Culture and Tourism Office. The analysis results show that in domestic tourist data, with parameters MinPts = 3 and ε = 1.00, one main cluster is formed consisting of 31 tourist locations and 7 noisy locations. In foreign tourist data, with ε = 0.6 and MinPts = 3, there is one cluster with 30 tourist locations and 8 other locations are categorized as noisy. Noisy locations tend to have higher visits but do not fit into the main cluster. These findings provide important insights for more targeted tourism promotion strategies and efficient resource allocation in East Java.
Tourist Preference Analysis Based on Google Reviews Using the DBSCAN Method Qori'atunnadyah, Marita; Murni, Cahyasari Kartika; Choiri, Achmad Firman; Marianto, Hadi; Yazid, Muhammad
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 5 Issue 2, October 2025
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol5.iss2.art7

Abstract

Tourism is a strategic sector contributing to regional economic growth. Although Lumajang Regency offers prominent natural destinations, data-based insights into tourist preferences remain limited. This study analyzed tourist preferences using Google Reviews through a text mining approach that integrated the density-based spatial clustering of applications with noise (DBSCAN) algorithm and lexicon-based sentiment analysis. Data were collected via web scraping from six major destinations, yielding 16,904 reviews, of which 9,800 contained analyzable text. The text data were preprocessed using the term frequency-inverse document frequency (TF–IDF) to generate numerical representations prior to clustering. Using DBSCAN with parameters ε = 0.8 and MinPts = 4, one main cluster comprising 9,353 reviews and 447 outliers was identified. The main cluster was dominated by keywords such as waterfall, beautiful, and scenery, emphasizing the visual appeal of Tumpak Sewu as Lumajang’s tourism icon, while the outliers reflected reviews from international visitors and practical travel information. Sentiment analysis showed that most reviews were positive (68.0%), followed by neutral (24.1%) and negative (7.9%). These findings indicate a predominantly positive perception of Lumajang tourism, though accessibility and facilities require improvement. The study demonstrates the potential of digital review data for developing data-driven tourism management and promotion strategies.
Co-Authors Choiri, Achmad Firman Marianto, Hadi Muhammad Yazid Murni, Cahyasari Kartika