Analisis Sentimen Sepak Bola Indonesia pada Twitter menggunakan K-Nearest Neighbors dan Random Forest

Prabowo, Dedy Agung and Sudianto, Sudianto (2023) Analisis Sentimen Sepak Bola Indonesia pada Twitter menggunakan K-Nearest Neighbors dan Random Forest. Analisis Sentimen Sepak Bola Indonesia pada Twitter menggunakan K-Nearest Neighbors dan Random Forest, 6 (2). pp. 217-227. ISSN 2614-3062

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Abstract

Twitter is one of the most widely used social media today. Twitter allows users to provide the latest news and comments about ongoing events in the World. In Indonesia, the final match of the AFF Suzuki Cup 2020 became a hot topic because, for the sixth time, Indonesia was runner-up after 2000, 2002, 2004, 2010, and 2016 appearances for the Indonesian national team. With so many opinions and criticisms circulating, distinguishing between positive and negative opinions takes a long time. Therefore, a sentiment analysis model is needed that can classify positive and negative opinions as evaluation material for the Indonesian National Team in the future. This study uses the K-Nearest Neighbors and Random Forest algorithm methods in sentiment analysis classification. The data comes from a reply to Joko Widodo's Twitter account regarding congratulations to the Indonesian national team after competing against Thailand at the AFF Suzuki Cup 2020. Based on the test results, the accuracy of the K-Nearest Neighbors algorithm is 75% better than the Random Forest algorithm, with an accuracy of 71%.

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