Pengaruh Text Preprocessing terhadap Analisis Sentimen Komentar Masyarakat pada Media Sosial Twitter (Studi Kasus Pandemi COVID-19)
|
Abstract
Keywords
Full Text:
PDFArticle Metrics
Abstract view : 3517 timesPDF - 4056 times
References
WHO. What is COVID-19?. who.int. https://www.who.int/news-room/q-a-detail/q-a-coronaviruses (accessed March, 28, 2020)
Situasi Terkini Perkembangan Coronavirus Disease (COVID-19) 18 Juni 2020. infeksiemerging.kemkes.go.id. kemkes.go.id. https://infeksiemerging.kemkes.go.id/situasi-infeksi-emerging/situasi-terkini-perkembangan-coronavirus-disease-covid-19-18-juni-2020 (accessed , June 18, 2020).
Rana, S, & Singh. A, Comparative Analysis of Sentiment Orientation Using SVM and Naïve Bayes techniques, 2016 2nd International Conference on Next Generation Computing Technologies, pp. 106-111, Oct. 2016.
Agastya, I. M. A. Pengaruh Stemmer Bahasa Indonesia terhadap Performa Analisis Sentimen Terjemahan Ulasan Film. Jurnal TEKNOKOMPAK, vol. 12, no. 1, pp. 18-23, Feb. 2018.
Nhlabano, V. V. & Lutu, P. E. N. (2018). Impact of Text Pre-processing on the Performance of Sentiment Analysis Models for Social Media Data. 2018 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD), 2018, doi: 10.1109/ICABCD.2018.8465135.
L. G. Irham, A., Adiwijaya, and U. N. Wisesty, “Klasifikasi Berita Bahasa Indonesia Menggunakan Mutual Information dan Support Vector Machine,” J. Media Inform. Budidarma, vol. 3, no. 4, pp. 284–292, 2019.
Krouska. A, Troussas. C, and Virvou. M, “The effect of preprocessing techniques on Twitter Sentiment Analysis,” in 2016 7th International Conference on Information, Intelligence, Systems & Applications (IISA), 2016.
Junita, V. & Bachtiar, F. A. Klasifikasi Aktivitas Manusia menggunakan Algoritme Decision Tree C4.5 dan Information Gain untuk Seleksi Fitur. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 3, no. 10, pp. 9426-9433, Oct. 2019.
Nugroho, A. Analisis Sentimen Pada Media Sosial Twitter Menggunakan Naive Bayes Classifier Dengan Ekstrasi Fitur N-Gram. Jurnal Sains Komputer & Informatika (J-SAKTI), vol. 2, no. 2, pp. 200-209, Sep. 2018.
Putra. M. F, Anisa. H, & Diyas. P, Analisis Pengaruh Normalisasi, TF-IDF, Pemilihan Feature-set Terhadap Klasifikasi Sentimen Menggunakan Maximum Entropy (Studi Kasus : Grab dan Gojek), e-Proceeding of Engineering, vol. 6, no.2, pp. 8520-8529, Aug. 2019.
Hamzah. A. Deteksi Bahasa untuk Dokumen Teks Berbahasa Indonesia. Seminar Nasional Informatika (semnasIF 2010), pp. A5-A13, Mei. 2010.
Ahuja, R. et al. (2019). The Impact of Features Extraction on the Sentiment Analysis. International Conference on Pervasive Computing Advances and Applications, Procedia Computer Science, 2019, pp. 341-348.
Nurfikri, F. S., MS Mubarok. & adiwijaya. News Topic Classification Using Mutual Information and Bayesian Network. In 2018 6th International Conference on Information and Communication Technology (ICoICT), pp. 162-166. IEEE, 2018.
I. Mathilda Yulietha and S. Al Faraby. Klasifikasi Sentimen Review Film Menggunakan Algoritma Support Vector Machine,” e-Proceeding Eng., vol. 4, no. 3, pp. 4740–4750, 2017.
Adiwijaya, U. N. Wisesty, E. Lisnawati, A. Aditsania, D. S. Kusumo, "Dimensionality Reduction using Principal Component Analysis for Cancer Detection based on Microarray Data Classification", Journal of Computer Science vol.14, no.11, pp.1521-1530, Nov. 2018.
Cahyanti, F. E., Adiwijaya, & S. Al Faraby. On The Feature Extraction For Sentiment Analysis of Movie Reviews Based on SVM. 8th International Conference on Information and Communication Technology (ICoICT) ), Yogyakarta, Indonesia, Jun. 2020.
Said Al Farabym Eliza Riviera R. J, Andina Kusumaningrum dan Adiwijaya, “Classification of hadith into positive suggestion, negative suggestion, and information, IOP, 2018.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Pengaruh Text Preprocessing terhadap Analisis Sentimen Komentar Masyarakat pada Media Sosial Twitter (Studi Kasus Pandemi COVID-19)
Refbacks
- There are currently no refbacks.
Copyright (c) 2021 JURNAL MEDIA INFORMATIKA BUDIDARMA
This work is licensed under a Creative Commons Attribution 4.0 International License.
JURNAL MEDIA INFORMATIKA BUDIDARMA
STMIK Budi Darma
Secretariat: Sisingamangaraja No. 338 Telp 061-7875998
Email: mib.stmikbd@gmail.com
This work is licensed under a Creative Commons Attribution 4.0 International License.