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All Journal Bulletin of Electrical Engineering and Informatics International Journal of Engineering, Science and Information Technology
Ketut Jaya Atmaja
Indonesian Institute of Business and Technology
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Unveiling Ubud’s Gastronomic Image through Comparative Aspect-Based Sentiment Analysis as Cross-Platform Insights and Strategic SWOT Perspectives Ni Wayan Sumartini Saraswati; Ketut Jaya Atmaja; I Wayan Dharma Suryawan; Christina Purnama Yanti
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1843

Abstract

Gastronomy is a strategic element in developing tourism destinations, and Ubud occupies a position as a cultural center that offers culinary riches of traditional value. This research reveals the gastronomic image of Ubud through a cross-platform analysis of TripAdvisor restaurant reviews and public opinion on sentiment labels at the micro level, implemented with VADER before fine-tuning aspect sentiment analysis (with BERT) to obtain a more granular representation. An in-depth analysis was conducted using wordcloud for cross-platform insights and SWOT recommendations. The research results show that the highest accuracy model evaluation results reached 98.87% for the term extraction aspect and 97.48% for the sentiment analysis aspect for TripAdvisor. Based on insight analysis, the food aspect is the main focus on both platforms, but with different narrative patterns: TripAdvisor emphasizes detailed evaluations such as taste, presentation, and service, while X is more oriented towards promotions, cultural identity, and participatory experiences, especially related to events such as the Ubud Food Festival. The integration of ABSA results into the SWOT framework resulted in four strategic findings: main strengths in the form of culinary authenticity, service quality, atmosphere, and experiential value; weaknesses related to inconsistencies in taste and chef quality; opportunities obtained from organizing festivals, street food, and culinary diversification; and threats in the form of overtourism and the perception of high prices. Overall, this study provides conceptual, methodological, and strategic contributions. The resulting findings strengthen the scientific basis for developing Ubud as a sustainable gastronomic destination that emphasizes taste, nature, and culture, as well as supporting data-based decision-making for tourism stakeholders.
Tourists' perceptions of Ubud as a world gastronomy destination: a modified ABSA-BERT analysis Ni Wayan Sumartini Saraswati; Ketut Jaya Atmaja; I Wayan Dharma Suryawan; Christina Purnama Yanti
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.11411

Abstract

Although Ubud has been designated by the United Nations World Tourism Organization (UNWTO) as a global gastronomy tourism destination, existing research remains limited in assessing its strengths and challenges from a data-driven tourist perspective. Prior studies largely rely on qualitative, supply-side approaches and conventional sentiment analysis that overlook specific experiential aspects. Moreover, the integration of multi-platform data and the application of modified deep learning-based aspect-based sentiment analysis (ABSA) models remain underexplored in gastronomy tourism. This study addresses these gaps by employing a modified ABSA-bidirectional encoder representations from transformers (ABSA-BERT) framework on data from TripAdvisor and social media X to provide a more comprehensive evaluation of tourist perceptions. The model incorporates predefined aspect-based aspect term extraction (ATE), valence aware dictionary and sentiment reasoner (VADER) lexicon labeling, and a novel algorithm for extracting aspect-level opinions. The results demonstrate strong performance, achieving 93.50% accuracy on X data and 91% on TripAdvisor. Findings indicate an overall positive perception of Ubud as a global gastronomic destination, particularly for its authentic local cuisine and appealing natural dining atmosphere, although challenges such as overly spicy dishes and uncomfortable seating arrangements remain.
Co-Authors Christina Purnama Yanti I Wayan Dharma Suryawan Saraswati, Ni Wayan Sumartini