Sentiment Analysis Tweet KTT G-20 di Media Sosial Twitter Menggunakan Metode Naïve Bayes

Authors

  • Arta Tirtayasa Fakultas Informatika, Institut Teknologi Telkom Purwokerto
  • Alfian Listiyo Wibowo Fakultas Informatika, Institut Teknologi Telkom Purwokerto

DOI:

https://doi.org/10.47747/jpsii.v4i2.1097

Keywords:

Sentiment Analysis, Twitter, Naïve Bayes, G-20

Abstract

The G-20 or The Group of Twenty is a group consisting of 19 countries with major economies plus 1 European Union. This group was formed in 1999 as a systematic forum with the aim of discussing important issues or problems related to the world economy. The countries included in the G-20 include Australia, Canada, Saudi Arabia, United States, India, Russia, South Africa, Turkey, Argentina, Brazil, Mexico, France, Germany, Italy, United Kingdom, China, India, Japan, and South Korea. From these data it can be concluded that the G-20 Summit is a forum capable of improving the standard of living of many people because of its ability to produce international policies, laws and regulations. Indonesia was once in the world's spotlight because in November 2022, Indonesia will host the G-20 Summit in Nusa Dua, Bali, to be precise. Ordinary people use Twitter to express emotions related to something, both negative and positive emotions. With the implementation of sentiment analysis data from tweets from 500 data tweets using the Naive Bayes algorithm, the result is an accuracy of 69%. The accuracy value with class precision for positive predictions is 78%, while the class precision accuracy value for negative predictions is 36%. The positive class recall accuracy value is 81%, while the negative class recall accuracy value is 32%.

 

 

References

Adinegoro, R. W., Dyar, E., 2}, W., & Arifiyanti, A. A. (2020). Aplikasi Website Sentiment Analysis Ulasan Tokopedia. Jurnal Informatika Dan Sistem Informasi (JIFoSI), 1(3), 963–971. http://jifosi.upnjatim.ac.id/index.php/jifosi/article/view/193

Astuti, W. R. D. (2020). Kerja Sama G20 dalam Pemulihan Ekonomi Global dari COVID-19. Andalas Journal of International Studies (AJIS), 9(2), 131. https://doi.org/10.25077/ajis.9.2.131-148.2020

Bhatia, S., Sharma, M., & Bhatia, K. K. (2018). Sentiment Analysis and Mining of Opinions. Studies in Big Data, 30(May), 503–523. https://doi.org/10.1007/978-3-319-60435-0_20

Darwis, D., Siskawati, N., & Abidin, Z. (2021). Penerapan Algoritma Naive Bayes Untuk Analisis Sentimen Review Data Twitter Bmkg Nasional. Jurnal Tekno Kompak, 15(1), 131. https://doi.org/10.33365/jtk.v15i1.744

Feldman, R., & Sanger, J. (2006). The Text Mining Handbook. In The Text Mining Handbook. https://doi.org/10.1017/cbo9780511546914

Gafatia, I. W. D., & Hadinata, N. (2021). Analisis Pro Kontra Vaksin Covid 19 Menggunakan Sentiment Analysis Sumber Media Sosial Twitter. Jurnal Pengembangan Sistem Informasi Dan Informatika, 2(1), 34–42. https://doi.org/10.47747/jpsii.v2i1.544

Hajnal, P. I. (2019). THE G20 Evolution, Interrelationships, Documentation (J. J. Krinton (ed.); Second Edi). Routledge.

Pangestu, G. T., & Rosyda, M. (2022). Sentiment Analysis Tweet Pilkada 2020 Saat Pandemik COVID-19 di Media Sosial Twitter Menggunakan Metode 1D Convolutional Neural Network. Jurnal Media Informatika Budidarma, 6(2), 1017. https://doi.org/10.30865/mib.v6i2.3765

Santi, P. N. P., Ardani, W., & Putri, I. A. S. (2022). Presidensi G20 sebagai Sarana Marketing dan Branding Pariwisata Indonesia serta Pengaruhnya terhadap Peningkatan Kunjungan Wisatawan pada Era Pandemi Covid-19 (Studi Kasus di Hotel Melia Bali). Lensa Ilmiah: Jurnal Manajemen Dan Sumberdaya, 1(1), 15–20. https://doi.org/10.54371/jms.v1i1.167

Santoso1, V. I., Virginia2, G., & Lukito3, Y. (2017). Penerapan Sentimen Analisis Pada Hasil Evaluasi Dosen Dengan Metode SVM. Jurnal Transformatika, 14(2), 72.

Siregar, R. R. A., Siregar, Z. U., & Arianto, R. (2019). Klasifikasi Sentiment Analysis Pada Komentar Peserta Diklat Menggunakan Metode K-Nearest Neighbor. Kilat, 8(1), 81–92. https://doi.org/10.33322/kilat.v8i1.421

Weiss, S. M. (2005). Text mining : predictive methods for analyzing unstructured information (S. M. Weiss (ed.)) [Book]. Springer. https://doi.org/10.1007/978-0-387-34555-0.

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Published

2023-03-15

How to Cite

Tirtayasa, A., & Listiyo Wibowo, A. (2023). Sentiment Analysis Tweet KTT G-20 di Media Sosial Twitter Menggunakan Metode Naïve Bayes. Jurnal Pengembangan Sistem Informasi Dan Informatika, 4(2), 1 - 12. https://doi.org/10.47747/jpsii.v4i2.1097