Analisi Sentimen Masyarakat Terhadap Objek Wisata Di Kabupaten Lahat Menggunakan Algoritma Support Vector Machine

Abstract

Nature tourism is one of the sectors that plays an important role in supporting the development of regional tourism, including in Lahat Regency, which has significant waterfall tourism potential. Currently, many visitors share their reviews and experiences through digital platforms such as Google Maps. This review can be used as a source of information to understand the public's evaluation of the quality of tourist attractions. This study aims to examine public perception of tourist attractions in Lahat Regency using the Support Vector Machine (SVM) method. Research data were collected through scraping from Google Maps, totaling 500 reviews from five tourist attractions, namely Curup Maung, Curup Buluh, Senyawe Waterfall, Panjang Waterfall, and Green Canyon. The research stages include data preprocessing, consisting of cleaning, case folding, normalization, tokenization, stopword removal, and stemming. After that, feature extraction was carried out using the TF-IDF method and the classification process using the SVM algorithm. Based on the research results, the Support Vector Machine (SVM) method is able to perform sentiment classification quite well, although the accuracy level varies for each tourist attraction. Curup Maung and Panjang Waterfall achieved the highest accuracy level of 90%. Nevertheless, most visitor reviews were dominated by negative sentiments. This indicates that there are still several aspects that need to be improved, particularly related to tourist facilities and services. This research is expected to serve as a consideration for tourism managers and local governments in efforts to improve management quality as well as the development of tourism in Lahat Regency.