Analisis Sentimen Terhadap Tayangan Televisi Berdasarkan Opini Masyarakat pada Media Sosial Twitter menggunakan Metode K-Nearest Neighbor dan Pembobotan Jumlah Retweet - Winda Estu Nurjanah; Rizal Setya Perdana; Mochammad Ali Fauzi (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2017)
Twitter is a social media that attracts many internet users as a media for communication and getting information. The information covered on Twitter in the form of questions, opinions or comments, whether it is positive or negative. Sentiment analysis is a part of research from Text Mining that conducted the classification process on text documents. K-Nearest Neighbor was used as method of this research, by adding the quality of retweet (non-textual). The result of textual quality of the K-Nearest Neighbor classification and the non-textual quality from the sum of retweets would be combined using certain constants (Î± and Î²) to generate positive and negative sentiments. The data was used in the form of public opinion on the television show on twitter showed 400. From the test results of accuracy using non-textual quality obtained 82.50%, using 60% non-textual quality, and use the combination of both was 83.33% with the score k=3 and the exact multiplication constant Î±=0,8 and Î²=0.2.