Analisis Sentimen pada review hotel menggunakan metode pembobotan dan klasifikasi - Aam Munir; Enda Putri Atika; Aziza Devita Indraswari (Lentera Dua Indonesia, 2022)
Globally, the tourism industry has an important role in the economic progress of a region or country. This development is assisted by the development of internet technology such as social media, tourism portal websites and others. The assessment of a hotel on the portal website can also affect the consumer's desire to choose the hotel or not. Sentiment analysis on reviews issued by consumers can be divided into positive reviews or negative reviews. Sentiment analysis starts from data retrieval, namely scrapping and then proceeds to the preprocessing process so that data is obtained that is ready for analysis. After the preprocessing process is carried out, it is continued with the weighting process. the weighting process uses three methods, namely Unigram, bigram and term frequency Inverse Document frequency. After the weighting process is carried out, the classification process is carried out using two methods, namely Naive Bayes and Support vector Machine. The result of the classification process is the highest accuracy obtained by the TF-IDf weighting method and the SVM method of 95% followed by the Unigram weighting method with the SVM method of 94%.