Analisis Sentimen Tentang Opini Performa Klub Sepak Bola Pada Dokumen Twitter Menggunakan Support Vector Machine Dengan Perbaikan Kata Tidak Baku - Swandy Raja Manaek Pakpahan; Indriati Indriati; Marji Marji (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
Football is one of the most popular sports in the world, including in Indonesia. A football club is very dependent on its supporters so that the satisfaction of supporters of a football club must be maintained. Supporters of football clubs themselves often provide arguments to a football club via Twitter media. Therefore, the authors propose research to build a sentiment analysis system for football club performance opinions on Twitter documents. This research uses the Support Vector Machine method and Levenshtein Distance for non-standard word correction. The process starts with preprocessing the data, then do word correction with Levenshtein Distance, weighting using Term Frequency-Inverse Document Frequency, followed by classification using Support Vector Machine. The test results with the highest accuracy were obtained at 83.25% with learning rate = 0,0001, complexity = 0,001, lambda = 0,1, epsilon = 0,0001 and maximum iteration = 50.