<![CDATA[Indonesia, as a country with significant growth in internet users, recorded a 7.3% digital economy contribution to GDP in 2017, surpassing the overall economic growth of 5.1%. One of the main challenges is efficiency in managing user reviews to improve services, as done by Bukalapak app using data scraping to collect 5000 reviews. This study uses the Naïve Bayes algorithm to analyze the sentiment of Bukalapak app user reviews, focusing on identifying positive and negative sentiment patterns. The goal is to deepen the understanding of user perceptions of Bukalapak services and provide a basis for strategic decision-making in improving user experience and application services. The Naïve Bayes algorithm in this study achieved an accuracy rate of 67.9%, with 13.3% of reviews found to be positive and 86.7% of reviews negative. The analysis results highlight the importance of improvements in certain aspects of Bukalapak's services, which can lead to further development to increase user satisfaction. The majority of Bukalapak reviews indicate shortcomings or criticism of its services, which highlights the importance of improvement in certain aspects. The Naïve Bayes model provides a clear understanding of user sentiment, which is key in strategic decision-making and efforts to improve user experience on the Bukalapak platform. Thus, this research makes an important contribution in directing further improvement and development steps in enhancing Bukalapak app services as well as better understanding user perceptions.]]>
