Analisis Sentimen Transportasi Online pada Twitter Menggunakan Metode Klasifikasi Naïve Bayes dan Support Vector Machine
DOI:
https://doi.org/10.22441/format.2021.v10.i1.009Keywords:
Transportasi online, analisis sentimen, Twitter, Naïve Bayes Classifier, Support Vector MachineAbstract
Transportasi online merupakan salah satu pilihan bagi masyarakat untuk berkegiatan sehari-hari baik saat bekerja, bepergian dan melakukan aktivitas lain. Salah satu cara untuk mengetahui persepsi masyarakat terhadap layanan transportasi online adalah dengan analisis sentimen seperti yang dilakukan pada penelitian ini. Data yang digunakan merupakan data valid dari sosial media Twitter untuk Transportasi online GrabId dan GojekIndonesia. Teknik analisis sentimen yang digunakan adalah Naïve Bayes Classifier dan metode Support Vector Machine (SVM). Keduanya digunakan untuk membandingkan tanggapan masyarakat dari analisis sentimen data tweet yang telah diklasifikasikan menjadi positif dan negatif. Berdasarkan penelitian ini didapatkan bahwa GrabId menggunakan metode SVM memberikan hasil class precision positif dan negatif yaitu 86.47% dan 46.67%, class recall positif dan negatif yaitu 96.21% dan 18.06%, accuracy 84.08%. Sedangkan untuk GojekIndonesia, metode SVM memberikan hasil yaitu class precision positif dan negatif yaitu 73.90% dan 35.65%, class recall positif dan negatif yaitu 89.84% dan 15.07%, accuracy 69.50%. Dari akurasi yang dihasilkan, metode SVM menghasilkan kinerja terbaik.Downloads
References
D. G. Nugroho, Y. H. Chrisnanto, and A. Wahana, “Analisis Sentimen Pada Jasa Ojek Online ... (Nugroho dkk.),” pp. 156–161, 2015.
A. Chan, M. Maharani, and P. W. Tresna, “Perbandingan Pengalaman Pengguna Pada Aplikasi Mobile Go-Jek Dan Grab (Studi Pada Konsumen Pt Go-Jek Dan Pt Grab Indonesia Di Dki Jakarta),” AdBispreneur, vol. 2, no. 2, 2017, doi: 10.24198/adbispreneur.v2i2.13183.
“Gojek - Wikipedia bahasa Indonesia, ensiklopedia bebas.” https://id.wikipedia.org/wiki/Gojek.
“Grab (perusahaan) - Wikipedia bahasa Indonesia, ensiklopedia bebas.” https://id.wikipedia.org/wiki/Grab_(perusahaan).
B. M. Pintoko and K. M. L, “Analisis Sentimen Jasa Transportasi Online pada Twitter Menggunakan Metode Naïve Bayes Classifier,” e-Proceeding Eng., vol. 5, no. 3, pp. 8121–8130, 2017.
F. AFSHOH, “Analisis Sentimen Menggunakan Naive Bayes Untuk Melihat Persepsi Masyarakat Terhadap Kenaikan Harga Jual Rokok Pada Media Sosial Twitter,” pp. 1–17, 2017.
M. . Imelda A.Muis & Muhammad Affandes, “Penerapan Metode SVM ( SVM ) Menggunakan Kernel Radial Basis Function ( RBF ) Pada Klasifikasi Tweet,” Sains, Teknol. dan Ind. Sultan Syarif Kasim Riau, vol. 12, no. 2, pp. 189–197, 2015.
A. T. J. H, “Preprocessing Text untuk Meminimalisir Kata yang Tidak Berarti dalam Proses Text Mining,” Inform. UPGRIS, vol. 1, pp. 1–9, 2015.
Downloads
Published
How to Cite
Issue
Section
License
The copyright to this article is transferred to Universitas Mercu Buana (UMB) if and when the article is accepted for publication. The undersigned hereby transfers any and all rights in and to the paper including without limitation all copyrights to UMB. The undersigned hereby represents and warrants that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required. The undersigned represents that he/she has the power and authority to make and execute this assignment.
We declare that this paper has not been published in the same form elsewhere.
Furthermore, I/We hereby transfer the unlimited rights of publication of the above-mentioned paper as a whole to UMB. The copyright transfer covers the right to reproduce and distribute the article, including reprints, translations, photographic reproductions, microform, electronic form (offline, online) or any other reproductions of similar nature.
The corresponding author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors. This agreement is to be signed by at least one of the authors who have obtained the assent of the co-author(s) where applicable. After submission of this agreement signed by the corresponding author, changes of authorship or in the order of the authors listed will not be accepted.
Retained Rights/Terms and Conditions
Although authors are permitted to re-use all or portions of the Work in other works, this does not include granting third-party requests for reprinting, republishing, or other types of re-use.
Our Articles are licensed under CC BY-NC
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
