Klasifikasi Sentimen Masyarakat di Twitter Terhadap Kenaikan Harga BBM dengan Metode Support Vector Machine

 (*)Siti Nurhaliza Mail (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia)
 Yusra Yusra (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia)
 Muhammad Fikry (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia)

(*) Corresponding Author

Submitted: June 11, 2023; Published: July 2, 2023

Abstract

The increase in the price of fuel oil (BBM) in Indonesia has always been a controversy which can be seen from online media such as Twitter which has an effect on the Indonesian economy, with this problem it has a change in the impact of cost instability due to an increase in fuel prices which will also affect the rate of increase in transportation costs and the rate of inflation. The effect of these changes leads to many different public opinions so as to produce pros and cons of these changes, with the existence of the problems above, the classification process is needed. This study uses 3000 tweet data obtained from the crawling process. This study obtains an accuracy of 85% at a ratio of 90:10, for a precision value of 85%, 99% recall and 91% f1-score for negative sentiment, while 83% precision value, 19% recall, 30% f1-score for positive sentiment. Then in the 80:20 comparison experiment, an accuracy of 83% was obtained, for a precision value of 83%, a recall of 99% and an f1-score of 91% for negative sentiment, while a precision value of 82%, a recall of 16%, an f1-score of 26% for positive sentiment.

Keywords


Support Vector Machine; Sentiment Analysis; Fuel Increase; Twitter; Classification

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References

Appannie.com, “State of Mobile 2022,” appannie.com, 2022. .

S. Merlinda, R. Aniqa, H. Alam, F. Ekonomi, and D. Bisnis, “Peranan Pemerintah melalui Intervensi Pasar dalam Perspektif Islam (Studi Kasus: Inflasi Harga BBM di Indonesia) Qorry Anggita Rishaq,” vol. 20, pp. 114–134, 2022.

B. Pamungkas, M. E. Purbaya, and D. J. A.K, “Analisis Sentimen Twitter Menggunakan Metode Support Vector Machine (SVM) pada Kasus Benih Lobster 2020,” J. Informatics, Inf. Syst. Softw. Eng. Appl., vol. 3, no. 2, pp. 10–20, 2021.

D. Darwis, E. S. Pratiwi, and A. F. O. Pasaribu, “Penerapan Algoritma Svm untuk Analisis Sentimen pada Data Twitter Komisi Pemberantasan Korupsi Republik Indonesia,” Edutic - Sci. J. Informatics Educ., vol. 7, no. 1, pp. 1–11, 2020.

M. R. A. Nasution and M. Hayaty, “Perbandingan Akurasi dan Waktu Proses Algoritma K-NN dan SVM dalam Analisis Sentimen Twitter,” J. Inform., vol. 6, no. 2, pp. 226–235, 2019.

Ferdi and Vina Ayumi, “Analisa Sentimen Mengenai Kenaikan Harga Bbm Menggunakan Metode Naïve Bayes dan Support Vector Machine,” JSAI (Journal Sci. Appl. Informatics), vol. 6, no. 1, pp. 1–10, 2023, doi: 10.36085/jsai.v6i1.4628.

E. Febriyani and H. Februariyanti, “Analisis Sentimen Terhadap Program Kampus Merdeka Menggunakan Naive Bayes Classifier di Twitter,” J. TeknoKompak, vol. 17, no. 1, pp. 25–38, 2023, doi: 10.30865/json.v4i2.5381.

F. D. Ananda and Y. Pristyanto, “Analisis Sentimen Pengguna Twitter Terhadap Layanan Internet Provider Menggunakan Algoritma Support Vector Machine,” MATRIK J. Manajemen, Tek. Inform. dan Rekayasa Komput., vol. 20, no. 2, pp. 407–416, 2021, doi: 10.30812/matrik.v20i2.1130.

I. Riadi, R. Umar, and F. D. Aini, “Analisis Perbandingan Detection Traffic Anomaly dengan Metode Naive Bayes dan Support Vector Machine (SVM),” Ilk. J. Ilm., vol. 11, no. 1, pp. 17–24, 2019, doi: 10.33096/ilkom.v11i1.361.17-24.

H. Tuhuteru and A. Iriani, “Analisis Sentimen Perusahaan Listrik Negara Cabang Ambon Menggunakan Metode Support Vector Machine dan Naive Bayes Classifier,” J. Inform. J. Pengemb. IT, vol. 3, no. 3, pp. 394–401, 2018, doi: 10.30591/jpit.v3i3.977.

A. D. Hartanto and N. K. Fitriyani, “Analisis Sentimen Terhadap Tokoh Publik Menggunakan Support Vector Machine,” MEANS (Media Inf. Anal. dan Sist., vol. 5, no. 1, pp. 8–12, 2020.

A. S. Rahayu and A. Fauzi, “Komparasi Algoritma Naïve Bayes dan Support Vector Machine (SVM) pada Analisis Sentimen Spotify,” J. Sist. Komput. dan Inform. Hal 349−, vol. 354, no. 2, pp. 349–354, 2022, doi: 10.30865/json.v4i2.5398.

L. Mutawalli, M. T. A. Zaen, and W. Bagye, “Klasifikasi Teks Sosial Media Twitter Menggunakan Support Vector Machine (Studi Kasus Penusukan Wiranto),” J. Inform. dan Rekayasa Elektron., vol. 2, no. 2, p. 43, 2019, doi: 10.36595/jire.v2i2.117.

D. W. Syahputra, B. Rahayudi, and L. Muflikhah, “Analisis Sentimen Twitter terhadap Kebijakan Pemberlakuan Pembatasan Kegiatan Masyarakat menggunakan Metode Support Vector Machine,” Fak. Ilmu Komputer, Univ. Brawijaya, vol. 6, no. 3, pp. 1067–1072, 2022.

M. Metode, S. Vector, M. Svm, and D. A. N. Asosiasi, “Analisis Sentimen Ulasan Aplikasi Tiktok di Google Play menggunakan Metode Support Vector Manchine (SVM) dan Asosiasi,” vol. 10, pp. 346–358, 2021.

W. Paulina, F. A. Bachtiar, and A. N. Rusydi, “Analisis Sentimen Berbasis Aspek Ulasan Pelanggan terhadap Kertanegara Premium Guest House Menggunakan Support Vector Machine,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 4, no. 4, pp. 1141–1149, 2020.

H. C. Husada and A. S. Paramita, “Analisis Sentimen pada Maskapai Penerbangan di Platform Twitter Menggunakan Algoritma Support Vector Machine (SVM),” Teknika, vol. 10, no. 1, pp. 18–26, 2021.

Y. Yusra and M. Fikry, “Klasifikasi Tweet E-Commerce dengan Menggunakan Metode Support Vector Machine,” J. CoreIT J. Has. Penelit. Ilmu Komput. dan Teknol. Inf., vol. 4, no. 2, p. 50, 2018, doi: 10.24014/coreit.v4i2.5205.

Styawati., N. Hendrastuty, A. R. Isnain, and A. Y. Rahmadhani, “Analisis Sentimen Masyarakat terhadap Program Kartu Prakerja pada Twitter dengan Metode Support Vector Machine,” J. Inform. J. Pengemb. IT, vol. 6, no. 3, pp. 150–155, 2021.

R. Darmawan, I. Indra, and A. Surahmat, “Optimalisasi Support Vector Machine (SVM) Berbasis Particle Swarm Optimization (PSO) pada Analisis Sentimen Terhadap Official Account Ruang Guru di Twitter,” J. Kaji. Ilm., vol. 22, no. 2, pp. 143–152, 2022, doi: 10.31599/jki.v22i2.1130.

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