Analisis Sentimen Masyarakat terhadap Hasil Quick Count Pemilihan Presiden Indonesia 2019 pada Media Sosial Twitter Menggunakan Metode Naive Bayes Classifier

Lingga Aji Andika, Pratiwi Amalia Nur Azizah, Respatiwulan Respatiwulan


Indonesia is one of the countries that adheres to a democratic system. In the course of a democratic system it is marked by periodic general elections. In 2019 Indonesia held a general election simultaneously to elect the President, DPR, DPRD and DPD. After the election, a lot of opinion arise within the community, including on social media twitter. One of the topics discussed was the results of the quick count of the presidential election. Therefore, a method that can be used to analyze sentiment from the quick count opinion is needed, that is naive Bayes method. The aims of this study are to find the best naive Bayes model and to classify sentiments. The result shows the best accuracy of 82.90% with α = 0.05. The classification obtained is 34.5% (471) positive tweets and 65.5% (895) negative tweets on the results of the quick count.

Keywords : sentiment analysis, naive Bayes classifier, elections, quick count

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