Opini Masyarakat Twitter terhadap Kandidat Bakal Calon Presiden Republik Indonesia Tahun 2024
Abstract
Registration for the 2024 presidential candidates began at the end of 2023, but the euphoria of the supporters of the 2024 presidential candidates began to be felt from the beginning of 2022. Several survey institutions released public opinions regarding several prospective 2024 presidential candidates. One of the approaches taken in the survey was by conducting direct interviews with the public. However, political dynamics can change the results of political surveys at great expense. Public opinion about the 2024 presidential candidates cannot only be acquired through direct interviews. Public opinion acquisition can also be done through social media such as Twitter. This article aims to find out public opinion on the candidates for the 2024 presidential candidate on Twitter social media. This article uses a Twitter dataset and data analysis tools using orange data mining. The crawling dataset was carried out using the hashtags #capres2024 and #presiden2024 and the keywords anies baswedan, prabowo subianto and ganjar pranowo with 10,000 tweet data in content written in Indonesian. Text preprocessing includes transformation, tokenization, filtering and normalization applied to data before analysis is carried out with topic modeling and sentiment towards the presidential candidates. The results of the word cloud analysis show a very high level of popularity for candidate Ganjar Pranowo, but the results of the sentiment analysis show that Ganjar Pranowo has a negative sentiment.
References
Mahawardana, P. P. O., Imawati, I. A. P. F., & Dika, I. W. (2022). Analisis Sentimen Berdasarkan Opini dari Media Sosial Twitter terhadap “Figure Pemimpin” Menggunakan Python. Jurnal Manajemen Dan Teknologi Informasi, 12(2), 50–56. https://ojs.mahadewa.ac.id/index.php/jmti/article/view/2111
Prianto, C., Harani, N. H., & Firmansyah, I. (2019). Analisis Sentimen Terhadap Kandidat Presiden Republik Indonesia Pada Pemilu 2019 di Media Sosial Twitter. Jurnal Media Informatika Budidarma, 3(4), 405. https://doi.org/10.30865/mib.v3i4.1549
Santoso, E. B., & Nugroho, A. (2019). Analisis Sentimen Calon Presiden Indonesia 2019 Berdasarkan Komentar Publik Di Facebook. Eksplora Informatika, 9(1), 60–69. https://doi.org/10.30864/eksplora.v9i1.254
Saputra, N., Nurbagja, K., & Turiyan, T. (2022). Sentiment Analysis of Presidential Candidates Anies Baswedan and Ganjar Pranowo Using Naïve Bayes Method. Jurnal Sisfotek Global, 12(2), 114. https://doi.org/10.38101/sisfotek.v12i2.552
Surokim, & Ariyani, Y. (2020). Perguruan Tinggi Dan Survei Politik Dalam Kontestasi Elektoral Di Jawa Timur Indonesia: Tinjauan Ekonomi Politik Dan Etis. Jurnal ASPIKOM JATIM, 1(September), 13–30.
Syamsurrijal, M., Nurmandi, A., Jubba, H., Hidayati, M., Baharuddin, T., & Qodir, Z. (2021). Prediction candidates and political parties in the presidential election 2024 in Indonesia based on twitter. ResearchSquare, 1–9. https://doi.org/10.21203/rs.3.rs-1058949
Vonega, D. A., Fadila, A., & Kurniawan, D. E. (2022). Analisis Sentimen Twitter Terhadap Opini Publik Atas Isu Pencalonan Puan Maharani dalam PILPRES 2024. Journal of Applied Informatics and Computing, 6(2), 129–135.
Wiguna, R. A. raffaidy, & Rifai, A. I. (2021). Analisis Text Clustering Masyarakat Di Twitter Mengenai Omnibus Law Menggunakan Orange Data Mining. Journal of Information Systems and Informatics, 3(1), 1–12. https://doi.org/10.33557/journalisi.v3i1.78
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