<![CDATA[The rapid growth of global halal tourism positions West Nusa Tenggara (NTB) Province strategically, requiring a rapid, adaptive system for evaluating service quality to meet tourists' digital needs. However, local government evaluations are hampered by the limitations of conventional sentiment analysis methods, which often generalise textual emotions without specifically examining the dimensions of sharia services. Therefore, this study develops an integrated hybrid model combining topic modelling algorithms and sentiment analysis for the context of halal destinations in NTB. This R&D study integrates Selenium-based text mining and web scraping to extract unstructured social media and online news data, Latent Dirichlet Allocation (LDA) to identify automated factors, and the Naïve Bayes algorithm to calculate the sentiment polarity of each factor. The LDA model successfully identified five key factors of tourist satisfaction. The sentiment analysis results show that digital responses are dominated by positive (38.0%) and neutral (61.0%) sentiment, with the highest satisfaction being security (71.4%), while infrastructure and health are critical areas for improvement. The Interactive Monitoring Dashboard, the output of this research, has been validated for usability using the System Usability Scale (SUS) with 15 NTB tourism stakeholders, achieving a SUS score of 88.0 and entering the "Very Good" (Grade A) category.]]>
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