SENTIMENT ANALYSIS OF INDONESIAN ELECTION 2024 USING THE K-NEAREST NEIGHBOR METHOD - Kurniawan, Rido Dwi; Muliawan, Joshua (Jurnal Teknik Informatika (Jutif), 2024)
The abstract of this research discusses the analysis of Indonesian public sentiment regarding the 2024 election as observed via Twitter. Sentiment graph Research uses the Natural Language Processing method and the K-Nearest Neighbor algorithm to classify sentiment as positive, neutral, or negative. The current era of globalization influences the rapid progress of information technology circulating in society, one of the intermediaries is through the social media Twitter. Twitter can be used as a means of conveying opinions regarding suggestions, criticism and public opinion. Currently social media has a big impact on building public political sentiment and preferences. The social media I took is Twitter so that people's Tweets related to elections can be used to see a picture of public opinion. There are various opinions of Twitter users with positive, neutral and negative sentiments. However, classifying sentiment from Twitter users requires quite a lot of time and effort due to the large number of tweets found. The aim of this research is to conduct a public sentiment analysis of public opinion regarding the 2024 election. Data was collected in October and December 2023. The results show that positive sentiment dominates with 76%, followed by neutral sentiment at 16%, and negative 6%. This analysis helps understand public opinion regarding the 2024 election on social media, especially Twitter.