Enhancing Hotel Services in the Industry 6.0 Era: Optimizing Customer Satisfaction through Sentiment Analysis

The main goals of proposed work are to a new SA approach with help of ML techniques that align with the principles of Industry 6.0, facilitating the analysis of customer’s feedback on hotel services, and that feedbacks are either closed type or open type. The proposed work develops a new SA approach that aim to do analysis on reviews that are given by customers with their previous experiences. The SA approach identifies comments of type NR and PR from customer sentiments on services that are offered by hotels. Moreover, our method enables access to comments and does analysis of sentences. The methodologies apply SA to divide big sentences into small sentences and then classified into NR and PR, and finally analyze the emotion of big sentence into NR or PR. The implementation is done using the MNB and BNB algorithms. The MNB Algorithm produces result with 81.5% and found to be more accurate. This approach aligns with Industry 6.0's emphasis on human-machine collaboration, data-driven decision-making and technological integration to enhance customer-centric practices within the hospitality sector.