Analisis Sentimen pada Aplikasi Grab di Google Play Store Menggunakan Support Vector Machine

Rizki Wahyudi, Gilang Kusumawardana

Abstract


Pada Google Play Store, pengguna sering membaca review pengguna lain dan reputasi aplikasi, sebelum mengunduh sebuah aplikasi. Hal ini membuat analisis review pengguna sangat menarik bagi pemilik aplikasi untuk mengambil keputusan di masa depan. Penelitian ini bertujuan menganalisis review pengguna aplikasi Grab pada Google Play Store, menggunakan analisis sentimen. analisis review pengguna ini menggunakan metode Support Vector Machine (SVM). Evaluasi yang diusulkan dilakukan pada lebih dari 1.000 review pengguna yang dikumpulkan dari aplikasi Grab Indonesia di Google play store. Hasil dari analisis menggunakan Support Vector Machine menghasilkan akurasi 85,54% dan Hasil Review positif yang paling sering  diulas adalah ”ovo”, sedangkan review negatif yang paling sering diulas adalah “driver”.

Keywords


Text Mining, Sentiment Analysis, Support Vector Machine

References


APJII. (2018). Penetrasi & Profil Perilaku Pengguna Internet Indonesia. Apjii, 51. Retrieved from www.apjii.or.id

Bo Pang, Lillian Lee, and Shivakumar Vaithyanathan. (2002). Thumbs up? sentiment classification using machine learning techniques. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 79–86.

Borele, P., & Borikar, D. A. (2016). An Approach to Sentiment Analysis using Artificial Neural Network with Comparative Analysis of Different Techniques. IOSR Journal of Computer Engineering, 18(2), 2278–2661. https://doi.org/10.9790/0661-1802056469

Desy Setyowati, (2019) "Asing hingga Lokal, Ini Lima Pesaing Gojek dan Grab di Indonesia" Wired, [Online]. Tersedia https://katadata.co.id/berita/2019/08/07/asing-hingga-lokal-ini-lima-pesaing-gojek-dan-grab-di-indonesia [Diakses: 25 Desember 2019].

Google, & TEMASEK. (2018). Report e-Conomy SEA 2018. 1–32. Retrieved from https://www.thinkwithgoogle.com/_qs/documents/6730/Report_eConomy_SEA_2018_by_Google_Temasek_v.pdf

Gorunescu, F. (2011). Data mining concepts, models, and techniques. Berlin: Acid-free paper

Hartmann, J., Huppertz, J., Schamp, C., & Heitmann, M. (2018). Comparing automated text classification methods. International Journal of Research in Marketing. doi:10.1016/j.ijresmar.2018.09.009

Ilmawan, Edi Winarko. (2015) Aplikasi Mobile untuk Analisis Sentimen pada Google Play. IJCCS, Vol.9, No.1. FMIPA UGM Yogyakarta.ISSN: 1978-1520.

Indrayuni, E. (2016). Analisa Sentimen Review Hotel Menggunakan Algoritma Support Vector Machine Berbasis Particle Swarm Optimization. Jurnal Evolusi Volume 4 Nomor 2 - 2016, 4(2), 20–27.

Johnson, F., & Gupta, S. (2012). Web Content Mining Techniques: A Survey. International Journal of Computer Applications, 47(11), 44–50. https://doi.org/10.5120/7236-0266

Liu, B. (2012). Sentiment Analysis and Opinion Mining. AAAI-2011 Tutorial. https://doi.org/10.2200/S00416ED1V01Y201204HLT016

Medhat, W., Hassan, A., & Korashy, H. (2014). Sentiment analysis algorithms and applications: A survey. Ain Shams Engineering Journal, 5(4), 1093–1113. https://doi.org/10.1016/j.asej.2014.04.011

N. Fitriyah, B. Warsito, and D. A. Maruddani, (2020). "Analisis Sentimen Gojek Pada Media Sosial Twitter Dengan Klasifikasi Support Vector Machine (SVM)," Jurnal Gaussian, vol. 9, no. 3, pp. 376-390. https://doi.org/10.14710/j.gauss.v9i3.28932

Play, Google. (2019). Goole Play Store. https://play.google.com/store. Diakses pada tanggal 1 Oktober 2019.

Sharma, A., & Dey, S. (2012). A Comparative Study of Feature Selection and Machine Learning Techniques for Sentiment Analysis. RACS'12, October 23-26, 2012. ACM 978-1-4503-1492-3/12/10.

Tripathy, A., Agrawal, A., & Rath, S. K. (2015). Classification of Sentimental Reviews Using Machine Learning Techniques. Procedia Computer Science, 57, 821–829. https://doi.org/10.1016/j.procs.2015.07.523

Viva Budy Kusnandar, (07 Agustus 2019) "Berapa Pangsa Pasar Jasa Layanan Transportasi Online Indonesia?". [Online]. Tersedia: https://databoks.katadata.co.id/datapublish/2019/10/05/berapa-pangsa-pasar-jasa-layanan-transportasi-online-indonesia

Watrianthos, R., Suryadi, S., Irmayani, D., Nasution, M., & Simanjorang, E. F. S. (2019). Sentiment analysis of traveloka app using naïve bayes classifier method. International Journal of Scientific and Technology Research, 8(7), 786–788. https://doi.org/10.31227/osf.io/2dbe4




DOI: https://doi.org/10.31294/ji.v8i2.9681

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Jurnal Informatika

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Index by:

 
 Published LPPM Universitas Bina Sarana Informatika with supported by Relawan Jurnal Indonesia

Jl. Kramat Raya No.98, Kwitang, Kec. Senen, Jakarta Pusat, DKI Jakarta 10450, Indonesia
Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License