Sentiment Analysis of the Popularity of Parties Supporting the 2024 Presidential Candidates on Twitter Using the Naive Bayes Classifier Algorithm
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Keywords:
Sentiment Analysis, political parties, twitter, naive bayes classifier, popularitas
Abstract
In accordance with the democratic system of government, Indonesia allows each political party or combination of parties running in the general election to nominate its own presidential and vice presidential candidates, as long as these candidates meet legal requirements. Presidential elections are scheduled for 2024. A political figure who wants to run for president at that time will have to rely heavily on public opinion for support. As the 2024 election approaches, political parties are increasingly turning to social media to spread their messages and increase their support. The aim of this research is to compare the level of support for the two leading candidates for president and vice president in 2024 on Twitter to determine the proportion of tweets that are positive, negative, or neutral.The aim of this research is to compare the level of support for the two main candidates for president and vice president in 2024 on Twitter to determine the proportion of tweets that are positive, negative, or neutral.
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References
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[2] S. A. Hussein and M. R. Kareem, “A PROPOSED ARABIC TEXT AND TEXT IMAGE CLASSIFICATION TECHNIQUE USING A URL ADDRESS ,” Xinan Jiaotong Daxue Xuebao/Journal Southwest Jiaotong Univ., vol. 54, no. 5, 2019, doi: 10.35741/issn.0258-2724.54.5.41.
[3] R. Saputra et al., “Menentukan Popularitas Calon Presiden dan Tren pada Pilpres 2019 menggunakan Algoritma DBSCAN,” Puzzle Res. Data Technol. Fak. Sains dan Teknol., vol. 1, p. 3, 2019.
[4] B. Gunawan, H. S. Pratiwi, and E. E. Pratama, “Sistem Analisis Sentimen pada Ulasan Produk Menggunakan Metode Naive Bayes,” J. Edukasi dan Penelit. Inform., vol. 4, no. 2, p. 113, 2018, doi: 10.26418/jp.v4i2.27526.
[5] E. Fitri, “Analisis Sentimen Terhadap Aplikasi Ruangguru Menggunakan Algoritma Naive Bayes, Random Forest Dan Support Vector Machine,” J. Transform., vol. 18, no. 1, p. 71, 2020, doi: 10.26623/transformatika.v18i1.2317.
[6] P. A. Permatasari, L. Linawati, and L. Jasa, “Survei Tentang Analisis Sentimen Pada Media Sosial,” Maj. Ilm. Teknol. Elektro, vol. 20, no. 2, p. 177, 2021, doi: 10.24843/mite.2021.v20i02.p01.
[7] D. J. Iskandar, “Pentingnya Partisipasi Dan Peranan Kelembagaan Politik Dalam Proses Pembuatan Kebijakan Publik,” J. Ilmu Adm. Media Pengemb. Ilmu dan Prakt. Adm., vol. 14, no. 1, pp. 17–35, 2017, doi: 10.31113/jia.v14i1.2.
[8] A. Annas and Z. Rusnaedy, “Journal of Government Civil Society,” J. Gov. Civ. Soc., vol. 3, no. 2, pp. 117–128, 2020.
[9] S. D. Raharjo and G. Wang, “Paper Review Text Mining Twitter,” 2020.
[10] R. Putra Perssela, R. Mahendra, and W. Rahmadianti, “Pemanfaatan Media Sosial Untuk Efektivitas Komunikasi,” J. Ilm. Mhs. Kuliah Kerja Nyata, vol. 2, no. 3, pp. 650–656, 2022, doi: 10.36085/jimakukerta.v2i3.4525.
[11] A. Rivaldy, H. A. Fedria Wowor, S. R. Maisya, and D. Safitri, “Penggunaan Twitter Dalam Meningkatkan Melek Politik Mahasiswa Ilmu Komunikasi Universitas Negeri Jakarta,” Perspekt. Komun. J. Ilmu Komun. Polit. dan Komun. Bisnis, vol. 5, no. 1, p. 41, 2021, doi: 10.24853/pk.5.1.41-48.
[12] Umbar Riyanto, “Analisis Perbandingan Algoritma Naive Bayes dan Support Vector Machine Dalam Mengklasifikasikan Jumlah Pembaca Artikel Online,” JIKA (Jurnal Inform., vol. 2, no. 2, pp. 62–72, Oct. 2019, doi: 10.31000/.v2i2.1521.
[13] A. Muzaki and A. Witanti, “Sentiment Analysis of the Community in the Twitter To the 2020 Election in Pandemic Covid-19 By Method Naive Bayes Classifier,” J. Tek. Inform., vol. 2, no. 2, pp. 101–107, 2021, doi: 10.20884/1.jutif.2021.2.2.51.
[14] P. B. N. Setio, D. R. S. Saputro, and Bowo Winarno, “Klasifikasi Dengan Pohon Keputusan Berbasis Algoritme C4.5,” Prism. Pros. Semin. Nas. Mat., vol. 3, pp. 64–71, 2020.
[15] D. W. Wibowo, M. Z. Abdullah, and J. D. Kristanto, “Penerapan Metode Tf-Idf Untuk Chatbot Pada Sistem Informasi Pelayanan Percetakan Online,” Semin. Inform. Apl. Polinema 2020, pp. 196–200, 2020.
[16] F. Sodik, B. Dwi, and I. Kharisudin, “Perbandingan Metode Klasifikasi Supervised Learning pada Data Bank Customers Menggunakan Python,” J. Mat., vol. 3, pp. 689–694, 2020, [Online]. Available: https://journal.unnes.ac.id/sju/index.php/prisma/article/view/37875.
[17] G. K. Locarso, “Analisis Sentimen Review Aplikasi Pedulilindungi Pada Google Play Store Menggunakan NBC,” J. Tek. Inform. Kaputama, vol. 6, no. 2, pp. 353–361, 2022.
[18] M. A. Firmansyah, N. Ramsari, and A. D. Rachmanto, “Rancang Bangun Sistem Informasi Penjualan Pada Toko Buku Kita Tasikmalaya Berbasis Web Menggunakan Framework Laravel 8,” J. Teknol. Inf. dan Komun., vol. 12, no. 1, 2022, doi: 10.56244/fiki.v12i1.498.
[19] A. Deviyanto and M. D. R. Wahyudi, “Penerapan Analisis Sentimen Pada Pengguna Twitter Menggunakan Metode K-Nearest Neighbor,” JISKA (Jurnal Inform. Sunan Kalijaga), vol. 3, no. 1, p. 1, 2018, doi: 10.14421/jiska.2018.31-01.
[20] I. Amri and A. P. Aji, “Rancang Bangun Sistem Aplikasi Penerimaan Siswa Baru Menggunakan Metode Agile Di Smk Modellink Kabupaten Sorong,” Insect (Informatics Secur. J. Tek. Inform., vol. 4, no. 2, p. 51, 2019, doi: 10.33506/insect.v4i2.557.
[21] M. T. Anjasmoros, Istiadi, and F. Marisa, “Seminar Nasional Hasil Riset Prefix-RTR ANALISIS SENTIMEN APLIKASI GO-JEK MENGGUNAKAN METODE SVM DAN NBC (STUDI KASUS: KOMENTAR PADA PLAY STORE),” Conf. Innov. Appl. Sci. Technol. (CIASTECH 2020), no. Ciastech, pp. 489–498, 2020.
[22] S. R. I. Rezeki, Y. Restiviani, and R. Zahara, “Penggunaan sosial media twitter dalam komunikasi organisasi (studi kasus pemerintah provinsi dki jakarta dalam penanganan covid-19),” J. Islam. Law Stud., vol. 04, no. 02, pp. 63–78, 2020, [Online]. Available: http://jurnal.uin-antasari.ac.id/index.php/jils/.
[23] R. Soekarta, “RANCANG BANGUN SISTEM INFORMASI AKADEMIK BERBASIS WEB ( Studi Kasus Universitas Muhammadiyah Sorong ),” 2015.
[24] K. H. Ermin, Hanif, N. R. Muntiari, and P. A. Ramadhani, “Penerapan Metode Certainty Factor untuk Mendiagnosa Penyakit Preekslamsia pada Ibu Hamil dengan Menggunakan Bahasa Pemrograman Python,” Insect (Informatics Secur. J. Tek. Inform., vol. 7, no. 2, pp. 63–71, 2022, doi: 10.33506/insect.v7i2.1818.
Published
2023-11-30
How to Cite
[1]
D. Faroek, M. Yusuf, and G. Syatauw, “Sentiment Analysis of the Popularity of Parties Supporting the 2024 Presidential Candidates on Twitter Using the Naive Bayes Classifier Algorithm”, antivirus, vol. 17, no. 2, pp. 216-227, Nov. 2023.
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