Pendekatan text mining terhadap review pengunjung hotel bintang 5 di Bali selama pandemi COVID-19

Abstract

Bali's tourism and hospitality industry is one of the sectors affected by the COVID-19 pandemic, which decreased from 528,883 arrivals to only 47 arrivals in 6 months. It certainly encourages business providers to continue to survive and adapt and look for ways to attract tourists to use their service attributes. In order to innovate or develop the hotel's attributes, the service providers should determine the customer's needs and preferences to generate their appropriate strategy. Five-star hotels in Bali are the hotels with the most rooms and won international awards for their luxury. Of course, the services and facilities offered must be comparable to the price paid by the customer. Service quality is one factor that affects customer satisfaction, where customer review in the era of technological developments is provided through big data in the online accommodation provider platform. Text mining can be chosen to collect review data to extract data and find out hotel attributes that have the most significant frequency in customer reviews of five-star hotels in Bali with a vast number of reviews and variations. With this method, service providers can be assisted in identifying needs, planning processes, and developing services and service quality to achieve customer satisfaction.