STUDY OF PERCEPTION AND WILLINGNESS TO TRAVEL IN BALI FROM PANDEMIC TO ENDEMIC TRANSITION OF COVID-19 BASED ON BIG DATA OF TWITTER USING MACHINE LEARNING

• Main Author: Jibril Hemdi, Ahmad
• Format: Final Project
• Language: Indonesia
• Subjects: Perencanaan wilayah
• Online Access: https://digilib.itb.ac.id/gdl/view/72665
• Institution: Institut Teknologi Bandung

The coronavirus disease (COVID-19) pandemic has severely affected to the Indonesia economic, including Bali which are relied on tourism sector. Researcher labeled the sentiment and intention of English- and bahasa-Language tweet that related to tourism in Bali Province. Then, the accuracy of three machine learning algorithm (Decision Tree, Random Forest, dan Support Vector Machine) in predicting sentiment and intention of the tweet was investigated. Support Vector Machine algorithm was performed the best accuracy for the sentiment and intention analysis in both tweet of English- and bahasa-Language. The sentiment of English tweet achieved an accuracy of 70%, while bahasa tweet reached an accuracy of 63%. Afterwards, the intention of English tweet achieved an accuracy of 79%, while bahasa tweet reached an accuracy of 63%. Accuracy value is represented the correctness of the labeled result in the sentiment and intention of Twitter user. The top 10 words of each sentiment and intention in both tweet of English- and bahasa-Language were gathered to be analyzed for identifying the condition of willingness to visit and not to visit Bali. The results of condition analysis in helping tourism restoration of Bali Province suggest controlling COVID-19 infection, ensure G20 safety, solve environmental and transportation problems, as well as ensure convenience in religious activities. The strategy for attracting in foreign tourists focuses on preparing tourist destinations, accommodating activities and special moments, providing various methods of traveling and visiting guides, and strengthening attractions, while those for attracting in domestic tourists can be focused on preparing tourist destinations along with their accommodations, accommodating activities especially for nature and culture tourism, developing transportation systems, and strengthening attractions.