Dwitama, Raja Zaidaan Putera
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Klasifikasi Sentimen Masyarakat Terhadap Prabowo Subianto Bakal Calon Presiden 2024 di Twitter Menggunakan Naïve Bayes Classifier Dwitama, Raja Zaidaan Putera; Yusra, Yusra; Fikry, Muhammad; Yanto, Febi; Budianita, Elvia
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.7071

Abstract

The Indonesian President who has served for 2 consecutive terms cannot nominate again to become President. The public's attitude towards the three presidential candidates, Prabowo Subianto, Anies Baswedan, and Ganjar Pranowo, who are predicted to run for the 2024 presidential election, is also a matter for netizens' opinions from which conclusions can be drawn. Testing will be carried out in this research using information collected from tweets posted by Twitter users. Naïve Bayes Classifier is a technique that will be applied for sentiment assessment. In the upcoming presidential election, this research will be a source when determining the presidential choice. 2100 tweets with the search keywords "Presidential Candidate" and "Prabowo Subianto" are data collected by dividing 1050 positive data and 1050 negative data. Then implementation was carried out using Google Colab starting from data processing (cleaning, case folding, tokenizing, normalization, negation handling, stopword removal, stemming) followed by classification using the Naïve Bayes Classifier. According to test findings using the Confusion Matrix with three experimental test data 90:10, 80:20 and 70:30. Obtained the highest accuracy results of 89%, with a precision value of 89.7%, 88.6% recall and 88.9% f1-score in the 90:10 trial test.