Analisis Sentimen Opini Publik Tentang Vaksin Booster Menggunakan Metode Support Vector Machine dan firefly Algorithm - RIfky Pujianto; Dadang Yusup; Tesa Nur Padilah (Peneliti.net, 2022)
Coronavirus is a viral epidemic that has swept across the world. Indonesia is one of the countries affected by the virus, so the government is trying to prevent the spread of the coronavirus so that not many people are exposed to the coronavirus. One of the government's efforts to prevent the spread of this virus is to create a free vaccination program. In January 2022, the government issued the latest vaccine, namely the booster vaccine. The emergence of the booster vaccine is slightly doubted by the public because of the many hoax news about this booster vaccine. This study aims to analyze the sentiment of public opinion on the emergence of the booster vaccine. The data used for this analysis comes from public opinion on Twitter. The data is taken using the crawling method. This research uses the support vector machine (SVM) method as a process for classifying public opinion and the firefly algorithm as an optimization of SVM parameters. There are 3 class labels used for classifiers, namely positive, negative, and neutral. A lot of data used after the pre-processing process is 2223 data which is then split into as much as 80% training data and 20% testing before entering the classification stage using the SVM method. The results of the classification using SVM produce an accuracy of 85% on the default parameters and after being optimized using the firefly algorithm it produces an accuracy of 86% with parameters C = 1.0–3.0, = 0.1-1.0.