Analisis Sentimen Pemilihan Presiden Indonesia Tahun 2019 Di Twitter Berdasarkan Geolocation Menggunakan Metode Naïve Bayesian Classification - Wiranto Horsen Silitonga; Jay Idoan Sihotang (TeIKa, 2019)
2019 Indonesian Presidential Election is crowded to be discussed in the real world and also cyberspace, specifically on Twitter. Everyone is free to agree on the 2019 Indonesian Presidential candidate pair. Opinion raises many opinions, not only positive or neutral opinions but there are also negative opinions. Twitter's is now one of the most effective and efficient promotional or campaign venues to attract supporters. In this case, the researcher will conduct research on community leaders who are running for the presidency of Indonesia. The research method used in this study is the Naïve Bayesian Classifier classification algorithm. The data used are Indonesian tweets with Jokowi (# Jokowi2Periode) and Prabowo (#PrabowoSandi) keywords totaling 1009 data tweets for 5 months starting from September 1, 2019 to 31 January 1, 2019. Indonesia, namely Jakarta, Bandung, Medan, and Surabaya. Each data will be taken manually by using the Geolocation API that has been provided by Twitter via a Twitter search. The results of the classification using the Naïve Bayesian Classifier algorithm received 839 positive tweets, 32 negative tweets, and 67 neutral tweets from 938 overall tweets, or in the form of a percentage, there were 90% containing positive sentimen, 3% negative, and 7% negative sentimen towards Mr. Joko Widodo. And 56 positive tweets, 6 negative tweets, and 8 neutral tweets from 70 overall tweets, or in the form of the percentage there are 80% positive sentimens, 9% negative sentimens, and 11% neutral sentimens towards Mr. Prabowo. The level of accuracy generated from the Naïve Bayesian Classifier algorithm itself for this study amounted to 77.62%.