ANALISIS SENTIMEN DAN KLASIFIKASI KATEGORI TERHADAP TOKOH PUBLIK PADA DATA TWITTER MENGGUNAKAN NAIVE BAYES CLASSIFIER; SENTIMENT ANALYSIS AND CATEGORY CLASSIFICATION OF PUBLIC FIGURE ON TWITTER DATA USING NAIVE BAYES CLASSIFIER

AHMAD FATHAN HIDAYATULLAH, Azhari SN

2014 | Disertasi | PROGRAM STUDI S2 ILMU KOMPUTER

Twitter has been used extensively by various segments of society. Hence, it can be a media that represent trending issues in public. The people habbits of posting tweet can be a refference to find out the public sentiment toward public figures. The needs of sentiment analysis toward public figures are usually necessary when people want to know the public sentiment and response toward the public figures especially before elections. This research analyzes and classifies tweets in Indonesian language using Naive Bayes Classifier combined with negation detection and term weighting feature using term frequency and TF-IDF. The classification in this research is classified based on sentiment about public figure's feature. Based on the evaluation of the application and RapidMiner tools, the accuration result shows that the term frequency feature gives better result than that of TF-IDF. The Support Vector Machine method gives better result than that of Naive Bayes in classifying tweet. However, both of these methods have the same good performance to classify tweet

Kata Kunci : analisis sentimen; klasifikasi; Naive Bayes; Support Vector Machine