Sentiment Analysis of Presidential Candidates Based on Tweets on Social Media Using the Naive Bayes Classifier
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Abstract
This research is to analyze the sentiments of the Indonesian people about the presidential candidates who are likely to advance in the 2024 presidential election from tweets on the Twitter application. Tweets on Twitter are written, typed and published by Indonesian netizens about the candidates who are likely to advance in the 2024 presidential election. In this study, researchers used tools, namely RapidMiner Studio to collect tweet data from Indonesian netizens about the candidates. Furthermore, the researcher uses the Naïve Bayes Classifier algorithm to determine whether a statement or sentiment has a positive or negative value which is carried out using Rapid Miner tools as well. Of the four candidates that the researchers examined, Anies got 74% positive sentiment 26% negative sentiment, then followed by Sandi, namely 57% positive sentiment 43% negative sentiment, Ganjar received 53% positive sentiment 47% negative sentiment and Prabowo received 32% positive sentiment. 68% negative sentiment. The conclusion of this research is to find out which candidates are liked or favored by the Indonesian people from the results of sentiment analysis using the Naïve Bayes algorithm and the tools used, namely Rapid Miner.
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References
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[3] N. Anas, “Komunikasi antara Kognitif dan Kemampuan Berbahasa,” EUNOIA (Jurnal Pendidik. Bhs. Indones., vol. 1, no. 1, pp. 1–8, 2021, doi: http://dx.doi.org/10.30829/eunoia.v1i1.997.
[4] R. D. Himawan and E. Eliyani, “Perbandingan Akurasi Analisis Sentimen Tweet terhadap Pemerintah Provinsi DKI Jakarta di Masa Pandemi,” J. Edukasi dan Penelit. Inform., vol. 7, no. 1, p. 58, 2021, doi: 10.26418/jp.v7i1.41728.
[5] S. R. I. Rezeki, “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, doi: http://dx.doi.org/10.18592/jils.v4i2.3804.
[6] T. M.Si., “Analisis Akses Dan Penggunaan Media Sosial Oleh Rumah Tangga Dan Individu Di Kota Batu Jawa Timur,” J. Komunika J. Komunikasi, Media dan Inform., vol. 7, no. 2, pp. 72–86, 2018, doi: 10.31504/komunika.v7i2.1627.
[7] W. Maulana and M. Mulyadi, “Ujaran Kebencian Terhadap Jokowi pada Masa Pandemi Covid-19: Studi Kasus Twitter,” J. Lisnguistik Komputasional, vol. 4, no. 1, pp. 27–33, 2021, doi: https://doi.org/10.26418/jlk.v4i1.42.
[8] R. Yunanto, A. P. Purfini, and A. Prabuwisesa, “Survei Literatur: Deteksi Berita Palsu Menggunakan Pendekatan Deep Learning,” J. Manaj. Inform., vol. 11, no. 2, pp. 118–130, 2021, doi: 10.34010/jamika.v11i2.5362.
[9] C.- Pandemic, B. Laurensz, and E. Sediyono, “Analisis Sentimen Masyarakat terhadap Tindakan Vaksinasi dalam Upaya Mengatasi Pandemi Covid-19 ( Analysis of Public Sentiment on Vaccination in Efforts to Overcome the,” J. Nas. Tek. Elektro dan Tekonolgi Inf., vol. 10, no. 2, pp. 118–123, 2021, doi: https://doi.org/10.22146/jnteti.v10i2.1421.
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[12] L. Ardiani, H. Sujaini, and T. Tursina, “Implementasi Sentiment Analysis Tanggapan Masyarakat Terhadap Pembangunan di Kota Pontianak,” J. Sist. dan Teknol. Inf., vol. 8, no. 2, p. 183, 2020, doi: 10.26418/justin.v8i2.36776.
[13] F. Sidik, I. Suhada, A. H. Anwar, and F. N. Hasan, “Analisis Sentimen Terhadap Pembelajaran Daring Dengan Algoritma Naive Bayes Classifier,” J. Linguist. Komputasional, vol. 5, no. 1, p. 34, 2022, doi: 10.26418/jlk.v5i1.79.
[14] A. S. Auliadaya, M. Rizki, and M. A. F. Azhary, “Analisa Pola Pembelian Produk Pada Toko Cimahi- Apriori,” Manaj. Inform., vol. 9, no. 1, pp. 58–69, 2019, doi: https://doi.org/10.34010/jamika.v9i1.1668.
[15] F. N. Hasan and M. Dwijayanti, “Analisis Sentimen Ulasan Pelanggan Terhadap Layanan Grab Indonesia Menggunakan Multinominal Naïve Bayes Classifier,” J. Linguist. Komputasional, vol. 4, no. 2, pp. 52–58, 2021, doi: https://doi.org/10.26418/jlk.v4i2.61.
[16] P. Arsi, R. Wahyudi, and R. Waluyo, “Optimasi SVM Berbasis PSO pada Analisis Sentimen Wacana Pindah Ibu Kota Indonesia,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 1, no. 10, pp. 231–237, 2021, doi: https://doi.org/10.29207/resti.v5i2.2698.
[17] E. Fitriani, “Perbandingan Algoritma C4.5 Dan Naïve Bayes Untuk Menentukan Kelayakan Penerima Bantuan Program Keluarga Harapan,” Sistemasi, vol. 9, no. 1, p. 103, 2020, doi: 10.32520/stmsi.v9i1.596.
[18] N. Legiawati, T. I. Hermanto, and Y. R. Ramadhan, “Analisis Sentimen Opini Pengguna Twitter Terhadap Perusahaan Jasa Ekspedisi Menggunakan Algoritma Naïve Bayes Berbasis PSO,” J. Ris. Komput., vol. 9, no. 4, pp. 930–937, 2022, doi: 10.30865/jurikom.v9i4.4629.
[19] A. Tangkelayuk and E. Mailoa, “Klasifikasi Kualitas Air Menggunakan Metode KNN , Naïve Bayes Dan Decision Tree,” JATISI, vol. 9, no. 2, pp. 1109–1119, 2022, doi: https://doi.org/10.35957/jatisi.v9i2.2048.
[20] J. Winahyu and I. Suharjo, “Aplikasi Web Analisis Sentimen Dengan Algoritma Multinomial Naïve Bayes,” Kumpul. Artik. Mhs. Pendidik. Tek. Inform., vol. 10, no. 2, p. 206, 2021, doi: 10.23887/karmapati.v10i2.36609.
[21] C. Nas, “Data Mining Prediksi Minat Calon Mahasiswa Memilih Perguruan Tinggi Menggunakan Algoritma C4.5,” J. Manaj. Inform., vol. 11, no. 2, pp. 131–145, 2021, doi: 10.34010/jamika.v11i2.5506.
[22] K. F. Irnanda, A. P. Windarto, and I. S. Damanik, “Optimasi Particle Swarm Optimization Pada Peningkatan Prediksi dengan Metode Backpropagation Menggunakan Software RapidMiner,” J. Ris. Komput., vol. 9, no. 1, pp. 122–130, 2022, doi: 10.30865/jurikom.v9i1.3836.
[23] D. Ardiansyah and W. Walim, “Algoritma c4.5 untuk klasifikasi calon peserta lomba cerdas cermat siswa smp dengan menggunakan aplikasi rapid miner,” J. Inkofar, vol. 1, no. 2, pp. 5–12, 2018, doi: https://doi.org/10.46846/jurnalinkofar.v1i2.29.
[24] P. Pasek, O. Mahawardana, G. Arya, I. P. Agus, and E. Pratama, “Analisis Sentimen Berdasarkan Opini dari Media Sosial Twitter terhadap ‘ Figure Pemimpin ’ Menggunakan Python,” JITTER-Jurnal Ilm. Teknol. dan Komput., vol. 3, no. 1, pp. 810–820, 2022, doi: https://doi.org/10.5281/zenodo.7177756.
[25] N. A. Rakhmawati, M. I. Aditama, R. I. Pratama, and K. H. U. Wiwaha, “Analisis Klasifikasi Sentimen Pengguna Media Sosial Twitter Terhadap Pengadaan Vaksin COVID-19,” J. Inf. Eng. Educ. Technol., vol. 4, no. 2, pp. 90–92, 2020, doi: 10.26740/jieet.v4n2.p90-92.
[26] H. Sulastomo, K. Gibran, and E. Maryansyah, “Analisis Sentimen Pada Twitter @ Ovo _ Id dengan Metode Support Vectore Machine ( SVM ),” J. Sains Komput. dan Inform., vol. 6, no. September, pp. 1050–1056, 2022, doi: http://dx.doi.org/10.30645/j-sakti.v6i2.514.