Assessing Tourist Interest Based on Gender Perceptions in Kayutangan Heritage through Sentiment Analysis of Google Point of Interest (POI)

Authors

  • Syahira Aulia Shalsabilla ITN Malang
  • Titik Poerwati Institut Teknologi Nasional Malang
  • Annisaa Hamidah Imaduddina
  • Firman Afrianto Ikatan Ahli Perencana Jawa Timur https://orcid.org/0000-0002-9369-8713

DOI:

https://doi.org/10.32493/jtsi.v8i2.54082

Keywords:

Kayutangan Heritage, Sentiment Analysis, Gender Perception, Tourists, Text Blob

Abstract

This study evaluates tourist interest at the Kayutangan Heritage area in Malang City based on gender perceptions through sentiment analysis of reviews on Google Point of Interest (POI). The research employs a big data approach by collecting reviews from Google Maps using web scraping techniques and processing them with the TextBlob algorithm to classify sentiments into positive, neutral, and negative categories. A total of 2,198 reviews were analyzed from six food and beverage (F&B) points across six spatial clusters of the Kayutangan Heritage area. The data were divided into two datasets—overall and gender-labeled—to identify sentiment tendencies among male and female tourists. The results indicate that female tourists tend to prefer Café Lafayette (Cluster 1.A), which offers women-friendly facilities such as separate restrooms and prayer rooms, with a positive sentiment of 67.6%. Meanwhile, male tourists are more interested in Kedai Sedjiwa (Cluster 2.B), which provides a clean environment, modern architecture, and a comfortable ambiance, generating 77.1% positive sentiment. The findings support Chebli et al.’s (2020) model of gender-based tourist preferences, demonstrating that men and women prioritize different elements of a destination. This study contributes to the development of gender-inclusive tourism strategies and data-driven management for heritage destinations.

References

Bulkrock, O., & Alsharman, N. (2024). A Natural Language Processing Approach for Sentiment Analysis of Hotel Reviews. International Journal of Advances in Soft Computing and Its Applications, 16(3), 15–32. https://doi.org/10.15849/IJASCA.241130.02

Calderón Fajardo, V., & Rodríguez Rodríguez, I. (2024). El turismo como espejo sociocultural: estereoripos y representaciones de género. IQual. Revista de Género e Igualdad, 7, 136–166. https://doi.org/10.6018/iqual.590801

Carballo, R. R., León, C. J., & Carballo, M. M. (2022). Gender as moderator of the influence of tourists’ risk perception on destination image and visit intentions. Tourism Review, 77(3), 913–924. https://doi.org/10.1108/TR-02-2021-0079

Castillo, J. H. B., Castro, K. D., Feleo, K. A. J. Q., Languban, J. L. N., Jr., M. O. V., & Hermosura, R. J. M. G. (2025). Gender Perspective: Challenges and Opportunities in Diverse Tourism Setting. International Journal of Innovative Science and Research Technology. https://api.semanticscholar.org/CorpusID:280812210

Chebli, A., Othmani, M. C., & Said, F. Ben. (2020). Market Segmentation in Urban Tourism: Exploring the Influence of Personal Factors on Tourists’ Perception. Journal of Tourism and Services, 11(20), 74–108. https://doi.org/10.29036/jots.v11i20.144

Dewi, S., & Arianto, D. B. (2023). Twitter Sentiment Analysis Towards Qatar as Host of the 2022 World Cup Using Textblob. Journal of Social Research, 2(2), 443–455. https://doi.org/10.55324/josr.v2i2.615

Domènech, A., Mohino, I., & Moya-Gómez, B. (2020). Using flickr geotagged photos to estimate visitor trajectories in world heritage cities. ISPRS International Journal of Geo-Information, 9(11). https://doi.org/10.3390/ijgi9110646

Gupta, C. P., & Kumar, V. V. R. (2024). A Study on Sustainable Tourism and Application of Sentiment Analysis in the Tourism Industry. 2024 International Conference on Emerging Techniques in Computational Intelligence (ICETCI), 52–57. https://api.semanticscholar.org/CorpusID:273227183

Hossen, M. S. (2020). Data Preprocess. In Machine Learning and Big Data (pp. 71–103). https://doi.org/https://doi.org/10.1002/9781119654834.ch4

Idris, I. H., Narawida, T., Agustin, R. D., Oktaviani, D., & Hidayat, M. (2023). Analisis RAPFISH Pada Studi Keberlanjutan Pembangunan Kawasan Wisata Heritage Kajoetangan di Kota Malang. Brawijaya Journal of Social Science. https://api.semanticscholar.org/CorpusID:259623821

Jamshed, H., Khan, M. S. A., Khurram, M., Inayatullah, S., & Athar, S. (2019). Data Preprocessing: A preliminary step for web data mining. 3C Tecnología_Glosas de Innovación Aplicadas a La Pyme, May, 206–221. https://doi.org/10.17993/3ctecno.2019.specialissue2.206-221

Jawale, S. (2023). Twitter Sentiment Analysis. Interantional Journal of Scientific Research in Engineering and Management, 07(04), 1–7. https://doi.org/10.55041/ijsrem18638

Kevin Perdana, Titania Pricillia, & Zulfachmi, Z. (2021). Optimasi Textblob Menggunakan Support Vector Machine Untuk Analisis Sentimen (Studi Kasus Layanan Telkomsel). Jurnal Bangkit Indonesia, 10(1), 13–15. https://doi.org/10.52771/bangkitindonesia.v10i1.120

Khakim, M. N. L., Putri, M. U. U., Suktianto, W., & Budi, N. A. (2019). Urgensi pengelolaan pariwisata Kampung Heritage Kajoetangan Malang. Jurnal Teori Dan Praksis Pembelajaran IPS, 4(1), 15–22. https://doi.org/10.17977/um022v4i12019p015

Liu, J., Zhu, Y., Liu, J., & Wang, P. (2025). Unraveling Tourist Behavioral Intentions in Historic Urban Built Environment: The Mediating Role of Perceived Value via SOR Model in Macau’s Heritage Sites. Buildings. https://api.semanticscholar.org/CorpusID:279890296

Malik, J. S., Goyal, P., & Sharma, M. A. K. (2010). A Comprehensive Approach Towards Data Preprocessing Techniques & Association Rules. https://api.semanticscholar.org/CorpusID:39245761

Manosso, F. C., & Ruiz, T. C. D. (2021). Using Sentiment Analysis in Tourism Research: A Systematic, Bibliometric, and Integrative Review. Journal of Tourism. https://api.semanticscholar.org/CorpusID:238633146

Martinez-Garcia, E., Raya-Vilchez, J. M., & Galí, N. (2018). Factors affecting time spent visiting heritage city areas. Sustainability (Switzerland), 10(6), 1–15. https://doi.org/10.3390/su10061824

Md Khairi, N. D., & Ismail, H. N. (2015). Acknowledging the Tourist Spatial Behavior for Space Management in Urban Heritage Destination. International Journal of Built Environment and Sustainability, 2(4), 317–323. https://doi.org/10.11113/ijbes.v2.n4.99

Mitra, I., & Sankar, M. M. (2021). Navigating the Insight of Gender Disparity Issues in Tourism: A Conceptual Study. Atna Journal of Tourism Studies, 15(1), 45–54. https://doi.org/10.12727/ajts.23.4

Murtikasari, R. A., & Tukiman, T. (2021). Development of Tourism Village Through Cbt Approach in Kayutangan Heritage Village, Malang City. Dia, 19(1), 314–327. https://doi.org/10.30996/dia.v19i1.5202

Osman, H., & Brown, L. (2024). Towards the search for a sustainable destination: a gender perspective. Journal of Sustainable Tourism, 32, 2344–2360. https://api.semanticscholar.org/CorpusID:269568072

Pramono, W. T., Anggriani, S. D., Meiji, N. H. P., Ujang, N., & Sayono, J. (2021). Awakening local tourism based on indische architecture in Indonesia. Case study Kajoetangan Kampong heritage of Malang. Geojournal of Tourism and Geosites, 35(2), 437–444. https://doi.org/10.30892/gtg.35223-670

Pung, J. M., Yung, R., Khoo-Lattimore, C., & del Chiappa, G. (2020). Transformative travel experiences and gender: a double duoethnography approach. Current Issues in Tourism, 23, 538–558. https://api.semanticscholar.org/CorpusID:198698826

Rachman, F. H., Imamah, & Rintyarna, B. S. (2022). Sentiment Analysis of Madura Tourism in New Normal Era using Text Blob and KNN with Hyperparameter Tuning. 2021 International Seminar on Machine Learning, Optimization, and Data Science (ISMODE), 23–27. https://api.semanticscholar.org/CorpusID:247796242

Remoaldo, P., Ghanian, M., & Alves, J. (2020). Exploring the experience of creative tourism in the northern region of Portugal—a gender perspective. Sustainability (Switzerland), 12(24), 1–17. https://doi.org/10.3390/su122410408

Sari, Y. D., & Muta’ali, L. (2025). Faktor-Faktor yang Mempengaruhi Minat Kunjungan Kembali Wisatawan ke Kawasan Kayutangan Heritage Kota Malang. Jurnal Nasional Pariwisata, 15(1), 1.

Downloads

Published

2025-04-30

How to Cite

Shalsabilla, S. A., Poerwati, T., Hamidah Imaduddina, A., & Afrianto, F. (2025). Assessing Tourist Interest Based on Gender Perceptions in Kayutangan Heritage through Sentiment Analysis of Google Point of Interest (POI). Jurnal Teknologi Sistem Informasi Dan Aplikasi, 8(2), 83–95. https://doi.org/10.32493/jtsi.v8i2.54082

Issue

Vol. 8 No. 2 (2025): Jurnal Teknologi Sistem Informasi dan Aplikasi

Section

Article

License

Copyright (c) 2025 Syahira Aulia Shalsabilla, Titik Poerwati, Annisaa Hamidah Imaduddina, Firman Afrianto

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).

Jurnal Teknologi Sistem Informasi dan Aplikasi have CC BY-NC or an equivalent license as the optimal license for the publication, distribution, use, and reuse of scholarly work.

In developing strategy and setting priorities, Jurnal Teknologi Sistem Informasi dan Aplikasi recognize that free access is better than priced access, libre access is better than free access, and libre under CC BY-NC or the equivalent is better than libre under more restrictive open licenses. We should achieve what we can when we can. We should not delay achieving free in order to achieve libre, and we should not stop with free when we can achieve libre.

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License

YOU ARE FREE TO:

  • Adapt - remix, transform, and build upon the material for any purpose, even commercially.
  • The licensor cannot revoke these freedoms as long as you follow the license terms