Analisis Sentimen Berbasis Aspek Pada Ulasan Google Maps - Pulungan, Ridson Al Farizal; Nugroho, Wisnu Adi Agung (Seminar Nasional Official Statistics, 2025)
West Papua is home to several internationally renowned tourist destinations, such as Raja Ampat and Cenderawasih Bay, making the tourism sector one of the key drivers of regional economic growth. However, restrictions on mobility and social interaction during the Covid-19 pandemic led to a significant decline in tourist arrivals in the province. Post-pandemic recovery strategies thus require timely and location-specific data. Google Maps Reviews represent a form of big data that is both up to date and geographically precise, making it useful for assessing and improving the quality of tourism services. This study employs the IndoBERT model for sentiment classification (None, Neutral, Positive, and Negative) across four aspects of tourism: attraction, facilities, accessibility, and price, as reflected in Google Maps reviews. The selected model demonstrates high performance, achieving an F1-score of 71.30% and an accuracy of 93.25%. Findings reveal that the pandemic significantly influenced visitor sentiment, evidenced by a rise in negative reviews during and after the pandemic. This suggests that existing recovery strategies have not been fully effective. Word cloud and thematic map analyses further indicate that the absence or inadequacy of basic facilities and poor accessibility are the primary complaints among tourists. Conversely, the price aspect remained relatively stable, with no substantial increase in negative sentiment, indicating that tourists are more sensitive to service quality than cost. These findings underscore the urgent need for comprehensive improvements in infrastructure and accessibility to support the post-pandemic recovery of tourism in West Papua.