Sentiment Analysis on Twitter(X) Related to Relocating the National Capital using the IndoBERT Method using Extraction Features of Chi-Square

 (*)Dufha Arista Mail (Telkom University, Bandung, Indonesia)
 Yuliant Sibaroni (Telkom University, Bandung, Indonesia)
 Sri Suryani Prasetyo (Telkom University, Bandung, Indonesia)

(*) Corresponding Author

Submitted: December 20, 2023; Published: January 24, 2024

Abstract

Sentiment analysis or commonly referred to as opinion mining is a field of science that can be used to get the percentage of positive sentiment and negative sentiment towards a person, company, institution, product, or even an issue or topic. Various topics are discussed on social media, one of which is Twitter (X). Starting from the economy, politics, social, culture, law and others. One of the most discussed topics on Twitter (X) is the transfer of Indonesia's capital city to East Kalimantan Province, which has drawn various opinions from netizens on Twitter (X). In this study, data regarding the transfer of the national capital taken by the author was taken from social media, namely from the social media Twitter (X) with a date range of January 1, 2022 to February 28, 2022. The method used in this research is IndoBERT using Chi-Square. Based on the experiments that have been carried out, the performance of IndoBERT with Chi-square selection features shows good results with an overall accuracy value of 94%, a precision value of 85%, a recall value of 91%, and an f1 value of 88.4% for all datasets.

Keywords


Sentiment Analysis; The Capital of The Country; IndoBERT; Chi-Square

Full Text:

PDF


Article Metrics

Abstract view : 198 times
PDF - 57 times

References

F. F. Noorikhsan, H. Ramdhani, B. C. Sirait, dan N. Khoerunisa, “Dinamika Internet, Media Sosial, dan Politik di Era Kontemporer: Tinjauan Relasi Negara-Masyarakat,” Journal of Political Issues, vol. 5, no. 1, hlm. 95–109, Jul 2023, doi: 10.33019/jpi.v5i1.131.

Nurhayati, A. E. Putra, L. K. Wardhani, dan Busman, “Chi-Square Feature Selection Effect On Naive Bayes Classifier Algorithm Performance For Sentiment Analysis Document,” dalam 2019 7th International Conference on Cyber and IT Service Management (CITSM), IEEE, Nov 2019, hlm. 1–7. doi: 10.1109/CITSM47753.2019.8965332.

A. H. Dyo fatra, N. H. Hayatin, dan C. S. K. Aditya, “Analisa Sentimen Tweet Berbahasa Indonesia Dengan Menggunakan Metode Lexicon Pada Topik Perpindahan Ibu Kota Indonesia,” Jurnal Repositor, vol. 2, no. 7, hlm. 977, Jul 2020, doi: 10.22219/repositor.v2i7.937.

H. Jayadianti, W. Kaswidjanti, A. T. Utomo, S. Saifullah, F. A. Dwiyanto, dan R. Drezewski, “Sentiment analysis of Indonesian reviews using fine-tuning IndoBERT and R-CNN,” ILKOM Jurnal Ilmiah, vol. 14, no. 3, hlm. 348–354, Des 2022, doi: 10.33096/ilkom.v14i3.1505.348-354.

H. K. Putra, M. A. Bijaksana, dan A. Romadhony, “Deteksi Penggunaan Kalimat Abusive Pada Teks Bahasa Indonesia Menggunakan Metode IndoBERT. ,” Jurnal Tugas Akhir Fakultas Informatika, 8(2), e-Proceeding of Engineering. ISSN: 2355-9365., 2021.

F. Koto, A. Rahimi, J. H. Lau, dan T. Baldwin, “IndoLEM and IndoBERT: A Benchmark Dataset and Pre-trained Language Model for Indonesian NLP,” dalam Proceedings of the 28th International Conference on Computational Linguistics, Stroudsburg, PA, USA: International Committee on Computational Linguistics, 2020, hlm. 757–770. doi: 10.18653/v1/2020.coling-main.66.

K. Sailunaz dan R. Alhajj, “Emotion and sentiment analysis from Twitter text,” J Comput Sci, vol. 36, hlm. 101003, Sep 2019, doi: 10.1016/j.jocs.2019.05.009.

N. I. P. Munggaran dan E. B. Setiawan, “DISC Personality Prediction with K-Nearest Neighbors Algorithm (KNN) Using TF-IDF and TF-Chi Square Weighting,” e-Proceedings Eng., vol. 6, no. 2, pp. 9446–9457, 2019..

A. Topbas, A. Jamil, A. A. Hameed, S. M. Ali, S. Bazai, dan S. A. Shah, “Sentiment Analysis for COVID-19 Tweets Using Recurrent Neural Network (RNN) and Bidirectional Encoder Representations (BERT) Models,” dalam 2021 International Conference on Computing, Electronic and Electrical Engineering (ICE Cube), IEEE, Okt 2021, hlm. 1–6. doi: 10.1109/ICECube53880.2021.9628315.

T. Ernayanti, M. Mustafid, A. Rusgiyono, dan A. R. Hakim, “PENGGUNAAN SELEKSI FITUR CHI-SQUARE DAN ALGORITMA MULTINOMIAL NAÏVE BAYES UNTUK ANALISIS SENTIMEN PELANGGGAN TOKOPEDIA,” Jurnal Gaussian, vol. 11, no. 4, hlm. 562–571, Feb 2023, doi: 10.14710/j.gauss.11.4.562-571.

F. Taufiqurrahman, S. Al Faraby, dan M. D. Purbolaksono, “Multi-Label Text Classification on Hadith Translation Indonesian Using Chi Square and SVM,” e-Proceedings Eng., vol. 8, no. 5, pp. 10650–10659, 2021..

Y. Widyaningsih, G. P. Arum, dan K. Prawira, “APLIKASI K-FOLD CROSS VALIDATION DALAM PENENTUAN MODEL REGRESI BINOMIAL NEGATIF TERBAIK,” BAREKENG: Jurnal Ilmu Matematika dan Terapan, vol. 15, no. 2, hlm. 315–322, Jun 2021, doi: 10.30598/barekengvol15iss2pp315-322.

K. Sailunaz dan R. Alhajj, “Emotion and sentiment analysis from Twitter text,” J Comput Sci, vol. 36, hlm. 101003, Sep 2019, doi: 10.1016/j.jocs.2019.05.009.

R. Man dan K. Lin, “Sentiment Analysis Algorithm Based on BERT and Convolutional Neural Network,” Proceedings of the 2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC). Guilin, China: IEEE, 2021.

J. Devlin, M.-W. Chang, K. Lee, dan K. Toutanova, “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,” Okt 2018, doi: https://doi.org/10.48550/arXiv.1810.04805.

Y. F. Saifullah dan A. S. Aribowo, “Comparison of Machine Learning for Sentiment Analysis in Detecting Anxiety Based on Social Media Data,” Jan. 2021, [Online]. Available: http://arxiv.org/abs/2101.06353..

M. I. Amal, E. S. Rahmasita, E. Suryaputra, dan N. A. Rakhmawati, “Analisis Klasifikasi Sentimen Terhadap Isu Kebocoran Data Kartu Identitas Ponsel di Twitter,” Jurnal Teknik Informatika dan Sistem Informasi, vol. 8, no. 3, Des 2022, doi: 10.28932/jutisi.v8i3.5483.

Y.-M. Kim dan T.-H. Lee, “Korean clinical entity recognition from diagnosis text using BERT,” BMC Med Inform Decis Mak, vol. 20, no. S7, hlm. 242, Sep 2020, doi: 10.1186/s12911-020-01241-8.

I. R. Hidayat dan W. Maharani, “General Depression Detection Analysis Using IndoBERT Method,” International Journal on Information and Communication Technology (IJoICT), vol. 8, no. 1, hlm. 41–51, Agu 2022, doi: 10.21108/ijoict.v8i1.634.

S. Hendrian, “Algoritma Klasifikasi Data Mining Untuk Memprediksi Siswa Dalam Memperoleh Bantuan Dana Pendidikan,” Faktor Exacta, vol. 11, no. 3, Okt 2018, doi: 10.30998/faktorexacta.v11i3.2777.

Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Sentiment Analysis on Twitter(X) Related to Relocating the National Capital using the IndoBERT Method using Extraction Features of Chi-Square

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 JURNAL MEDIA INFORMATIKA BUDIDARMA

Creative Commons License
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

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