Data warehouse development based on public sentiment analysis towards Bali tourism

The tourism industry, significantly impacted by the COVID-19 pandemic, is gradually recovering, with Bali aiming to attract 4.5 million visitors in 2023. This study explores the application of sentiment analysis and data warehousing in the tourism sector to understand tourist perceptions and support strategic decision-making. The research integrates sentiment analysis into a data warehouse system using the Extract, Transform, Load (ETL) process, enabling efficient data management and real-time analysis. Data was collected from Twitter and Instagram, covering comments from 2020 to June 2024, with sentiment classification achieving an accuracy of 87.38%, a precision of 0.8753, a recall of 0.8738, and an F1-score of 0.8678. This approach facilitates effective tourism management by identifying popular destinations, optimizing marketing strategies, improving services, and planning infrastructure development. The findings of this study highlight the importance of leveraging advanced data analytics for sustainable tourism development in Bali.