Abstract
At this time sentiment analysis is very widely used by people to see the extent of people's sentiments towards an object. Objects that can be used in sentiment analysis can be various kinds, for example about the product regarding receipt by consumers, agencies or institutions regarding the performance of the agency. Whereas for this study taking sentiment analysis of the State Institution namely the General Election Commission (KPU) about the sentiments of the implementation of the ELECTION simultaneously and also the results of the implementation of the ELECTION which have become the subject of discussion by netizens on social media. So this research takes retweet data and retention comments from Twitter social media users. The algorithm used in this study is Support Vector Machine (SVM), with optimization of the use of Weight by Correlation Feature Selection (FS). The results of cross validation SVM without FS are 66.49% for accuracy and 0.716 for AUC. Whereas SVM with FS is 81.18% for accuracy and 0.943 for AUC. Very significant improvement with the use of Weight by Correlation Feature Selection (FS).
Highlights
At this time sentiment analysis is very widely used by people to see the extent of people's sentiments
Objects that can be used in sentiment analysis can be various kinds
agencies or institutions regarding the performance of the agency
Summary
Bangsa Indonesia belum lama ini telah melakukan hajatan besar demokrasi yaitu PEMILU ( Pemilihan Umum). Yang berbeda dengan Pemilu sebelumnya adalah pelaksanaan untuk Pemilihan Calon Legislatif maupun Presiden dilakukan secara bersamaan. Yang dinilai oleh para pemilih bahwa Pemilu ini berjalan tidak sesuai dengan aturan yang ada. Mulai dari aroma kecurangan banyak disuarakan netizen, ketidaknetralan para penegak hukum terhadap salah satu calon pasangan presiden dan wakil presiden, serta pelaksanaan yang tidak JURDIL atau Jujur dan Adil. Semuanya banyak disuarakan lewat media sosial salah satunya adalah twitter. Umum) selaku penyelenggara hajatan besar ini tak optimasi pada algoritma klasifikasi adalah dengan lepas dari tuduhan-tuduhan yang dilontarkan oleh menggunakan algoritma Naïve Bayes dan optimasi sebagian pemilih yang merasa tidak puas dengan feature selection Information Gain yang hanya pelaksanaan Pemilu kali ini. Sentimen yang diberikan menaikan sebesar accuracy 0.85% untuk sentimen kepada KPU lewat media sosial merupakan gambaran analis pada movie review [4].
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