Analisis Sentimen Terhadap Vaksinasi Astra Zeneca pada Twitter Menggunakan Metode Naïve Bayes dan K-NN - Ramadhani, Slamet Harry; Wahyudin, Muhammad Iwan (Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), 2022)
The number of positive examples of Coronavirus continues to grow every day, especially in Indonesia. In an effort to reduce the surge in the higher case, the government carried out vaccination programs provided free for all Indonesian people. One vaccine given to Masyara-kat is the Astra Zeneca vaccine. In the provision of these vaccines bring benefits and losses in the community, some are supported and doubtful, some even refuse. On social media Twitter, Astra Zeneca is one of the most widely discussed in social media because of the many opinions or opinions that have sprung up from various circles. Some opinions from the community on Twitter will be used as data to examine the analysis of sentiment in the Astra Zeneca vaccine that utilizes the Naïve Bayes and K-NN methods. It is expected to produce an accurate level of accuracy. Based on the results of the study found different levels of accuracy, for the use of the Naïve Bayes method produced an accuracy rate of 90.71% +/- 4.66% (Micro Average: 90.77%) while the KNN method produced an accuracy rate of 74.78% +/- 3.74% (micro Average: 74.77%).
Keywords: Astra Vaccine Sentiment Analysis; Zeneca; Naive Bayes; K-NN