Analisis Sentimen Terhadap Pendapat Masyarakat Mengenai Pilkada 2024 Menggunakan Metode Support Vector Machine (SVM)
Kata Kunci:
analisis sentimen, pilkada, root cause analysis, support vector machine, twitter/xAbstrak
Naskah ini akan di terbitkan di JTIIK
Referensi
Atmojo, M. I. T., & Sinduningrum, E. (2023). Analisis Sentimen Tentang Penggunaan Galon Bebas BPA di Indonesia Menggunakan Algoritma Support Vector Machine. Jurnal Sistem Komputer Dan Informatika (JSON), 5(2), 394–403. https://doi.org/10.30865/JSON.V5I2.7101
Brahimi, B., Touahria, M., & Tari, A. (2021). Improving sentiment analysis in Arabic: A combined approach. Journal of King Saud University - Computer and Information Sciences, 33(10), 1242–1250. https://doi.org/10.1016/J.JKSUCI.2019.07.011
Gangidi, P. (2019). A systematic approach to root cause analysis using 3 × 5 why’s technique. International Journal of Lean Six Sigma, 10(1), 295–310. https://doi.org/10.1108/IJLSS-10-2017-0114/FULL/XML
Haddi, E., Liu, X., & Shi, Y. (2013). The Role of Text Pre-processing in Sentiment Analysis. Procedia Computer Science, 17, 26–32. https://doi.org/10.1016/J.PROCS.2013.05.005
Hendrastuty, N., Rahman Isnain, A., & Yanti Rahmadhani, A. (2021). Analisis Sentimen Masyarakat Terhadap Program Kartu Prakerja Pada Twitter Dengan Metode Support Vector Machine. Jurnal Informatika: Jurnal Pengembangan IT, 6(3), 150–155. https://doi.org/10.30591/JPIT.V6I3.2870
Husada, H. C., & Paramita, A. S. (2021). Analisis Sentimen Pada Maskapai Penerbangan di Platform Twitter Menggunakan Algoritma Support Vector Machine (SVM). Teknika, 10(1), 18–26. https://doi.org/10.34148/TEKNIKA.V10I1.311
Kannan, S., & Gurusamy, V. (2014). Preprocessing techniques for text mining. International Journal of Computer Science & Communication Networks, 5(1), 7–16. https://www.academia.edu/download/54879053/PreprocessingTechniquesforTextMining.pdf
Lestari, D. (2019). Pilkada DKI Jakarta 2017 : Dinamika Politik Identitas di Indonesia. JUPE : Jurnal Pendidikan Mandala, 4(4), 12–16. https://doi.org/10.58258/JUPE.V4I4.677
Paramarta, M., & Darmawan, J. B. B. (2023). Implementasi Metode Support Vector Machine dalam Analisis Sentimen Opini Masyarakat Terhadap Pilkada 2020 pada Media Sosial Twitter. 836–841. http://journal.itny.ac.id/index.php/ReTII
Puspitasari, A. M., Ratnawati, D. E., & Widodo, A. W. (2018). Klasifikasi Penyakit Gigi Dan Mulut Menggunakan Metode Support Vector Machine. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(2), 802–810. https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/967
Singh, V., Singh, G., Rastogi, P., & Deswal, D. (2018). Sentiment analysis using lexicon based approach. PDGC 2018 - 2018 5th International Conference on Parallel, Distributed and Grid Computing, 13–18. https://doi.org/10.1109/PDGC.2018.8745971
Soares Ito, A., Ylipää, T., Gullander, P., Bokrantz, J., & Skoogh, A. (2022). Prioritisation of root cause analysis in production disturbance management. International Journal of Quality and Reliability Management, 39(5), 1133–1150. https://doi.org/10.1108/IJQRM-12-2020-0402/FULL/PDF
Atmojo, M. I. T., & Sinduningrum, E. (2023). Analisis Sentimen Tentang Penggunaan Galon Bebas BPA di Indonesia Menggunakan Algoritma Support Vector Machine. Jurnal Sistem Komputer Dan Informatika (JSON), 5(2), 394–403. https://doi.org/10.30865/JSON.V5I2.7101
Brahimi, B., Touahria, M., & Tari, A. (2021). Improving sentiment analysis in Arabic: A combined approach. Journal of King Saud University - Computer and Information Sciences, 33(10), 1242–1250. https://doi.org/10.1016/J.JKSUCI.2019.07.011
Gangidi, P. (2019). A systematic approach to root cause analysis using 3 × 5 why’s technique. International Journal of Lean Six Sigma, 10(1), 295–310. https://doi.org/10.1108/IJLSS-10-2017-0114/FULL/XML
Haddi, E., Liu, X., & Shi, Y. (2013). The Role of Text Pre-processing in Sentiment Analysis. Procedia Computer Science, 17, 26–32. https://doi.org/10.1016/J.PROCS.2013.05.005
Hendrastuty, N., Rahman Isnain, A., & Yanti Rahmadhani, A. (2021). Analisis Sentimen Masyarakat Terhadap Program Kartu Prakerja Pada Twitter Dengan Metode Support Vector Machine. Jurnal Informatika: Jurnal Pengembangan IT, 6(3), 150–155. https://doi.org/10.30591/JPIT.V6I3.2870
Husada, H. C., & Paramita, A. S. (2021). Analisis Sentimen Pada Maskapai Penerbangan di Platform Twitter Menggunakan Algoritma Support Vector Machine (SVM). Teknika, 10(1), 18–26. https://doi.org/10.34148/TEKNIKA.V10I1.311
Kannan, S., & Gurusamy, V. (2014). Preprocessing techniques for text mining. International Journal of Computer Science & Communication Networks, 5(1), 7–16. https://www.academia.edu/download/54879053/PreprocessingTechniquesforTextMining.pdf
Lestari, D. (2019). Pilkada DKI Jakarta 2017 : Dinamika Politik Identitas di Indonesia. JUPE : Jurnal Pendidikan Mandala, 4(4), 12–16. https://doi.org/10.58258/JUPE.V4I4.677
Paramarta, M., & Darmawan, J. B. B. (2023). Implementasi Metode Support Vector Machine dalam Analisis Sentimen Opini Masyarakat Terhadap Pilkada 2020 pada Media Sosial Twitter. 836–841. http://journal.itny.ac.id/index.php/ReTII
Puspitasari, A. M., Ratnawati, D. E., & Widodo, A. W. (2018). Klasifikasi Penyakit Gigi Dan Mulut Menggunakan Metode Support Vector Machine. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(2), 802–810. https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/967
Singh, V., Singh, G., Rastogi, P., & Deswal, D. (2018). Sentiment analysis using lexicon based approach. PDGC 2018 - 2018 5th International Conference on Parallel, Distributed and Grid Computing, 13–18. https://doi.org/10.1109/PDGC.2018.8745971
Soares Ito, A., Ylipää, T., Gullander, P., Bokrantz, J., & Skoogh, A. (2022). Prioritisation of root cause analysis in production disturbance management. International Journal of Quality and Reliability Management, 39(5), 1133–1150. https://doi.org/10.1108/IJQRM-12-2020-0402/FULL/PDF
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