Sentiment Analysis of Indonesian Figure using Support Vector Machine

Suharyo Herwasto (Informatics Department, Universitas Islam Sultan Agung, Indonesia)
Imam Much Ibnu Subroto (Informatics Department, Universitas Islam Sultan Agung, Indonesia)
Badieah Assegaf (Informatics Department, Universitas Islam Sultan Agung, Indonesia)

Journal of Telematics and Informatics
Vol 6, No 3: September 2018

On the political year 2018 will be mutually popping reverberated figures for Indonesian presidential candidate 2019. The figures recognition process generally are now using social media, so it would appear the opinions of social media users. Opinions that appeared not only contain positive and negative polarity, but also contain a sentence of subjective and objective. By using a machine learning algorithm, namely Support Vector Machine, made sentiment analysis. The results of the analysis of this sentiment more optimally use the kernel Linear with the F-Measure of Polarity 68%, 68%, 63%, and the F-Measure Subjectivity 73%, 77%, 75% for each figure Anies Baswedan, Joko Widodo, and Prabowo Subianto.