Proceedings of the 1st International Conference on Sustainable Management and Innovation, ICoSMI 2020, 14-16 September 2020, Bogor, West Java, Indonesia

Research Article

Content Analysis of Tourist Opinion based on Tourism Quality (TOURQUAL) by Text Mining Online Reviews : The Case of Borobudur

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  • @INPROCEEDINGS{10.4108/eai.14-9-2020.2304462,
        author={Risca Septi Widyawati and Herry  Irawan and Astri  Ghina},
        title={Content Analysis of Tourist Opinion based on Tourism Quality (TOURQUAL) by Text Mining Online Reviews : The Case of Borobudur},
        proceedings={Proceedings of the 1st International Conference on Sustainable Management and Innovation, ICoSMI 2020, 14-16 September 2020, Bogor, West Java, Indonesia},
        publisher={EAI},
        proceedings_a={ICOSMI},
        year={2021},
        month={5},
        keywords={borobudur user generated content tourism quality text mining},
        doi={10.4108/eai.14-9-2020.2304462}
    }
    
  • Risca Septi Widyawati
    Herry Irawan
    Astri Ghina
    Year: 2021
    Content Analysis of Tourist Opinion based on Tourism Quality (TOURQUAL) by Text Mining Online Reviews : The Case of Borobudur
    ICOSMI
    EAI
    DOI: 10.4108/eai.14-9-2020.2304462
Risca Septi Widyawati1,*, Herry Irawan1, Astri Ghina1
  • 1: Telkom University
*Contact email: septirisca@student.telkomuniversity.ac.id

Abstract

The development of technology creates new phenomena that affect tourist behavior after visiting tourism destinations, one of the examples is exchange travel information and opinion of satisfaction or dissatisfaction with travel experiences through online review sites. The purpose of this research is to gain a deeper understanding of perceived destination-based tourism quality (TOURQUAL) using big data approach. This research applied selected text mining methods to investigates tourists’ perceptions of Borobudur. User-generated content collected from TripAdvisor between 2016 and 2019 were processed. Through sentiment analysis, Borobudur has a good service quality with 83.4% positive and 16.6% negative sentiments. Then, all reviews were grouped into six TOURQUAL attributes using multiclass classification. The top 3 positive attributes are access, experience, and technical quality. Through a text network analysis, we found the summary of tourists’ perceptions in the form of a network of the most frequent words used in social conversation. This research derives insights that useful to help businesses, especially the tourism industry to understand their visitors in a better way to improve their service quality performance.