Sentimen Analisis Masyarakat Indonesia di Twitter Terkait Metaverse dengan Algoritma Support Vector Machine

Main Article Content

Ali Ahmad
Windu Gata

Abstract

Metaverse is part of the increasingly rapid development of technology in the world, bringing the virtual world into the real world is very possible. Starting from a novel, metaverse has now begun the process of being implemented, especially with the COVID-19 pandemic being one of the strong foundations for speeding up the implementation of this technology. Since the emergence of the metaverse echoed by Facebook, which has changed its name to meta, has made the world's public attention increasingly highlight this technology, some have welcomed it and some have concerns about the development of this technology. Research to explore the sentiments of the Indonesian people towards metaverse technology uses the CRISP-DM method with the Support Vector Machine algorithm and the test is carried out by comparing it with another algorithm, namely the tree algorithm, the programming language used is the R language with the Rstudio application. This study obtained the results of Indonesian public opinion on metaverse technology which showed 66% to be neutral, 17% negative and 16% positive, while the results of testing with the SVM algorithm showed SVM performance results of 87% with the kernel used was Linear, and these results are far better than using the tree algorithm which only has a performance of 71%.

Downloads

Download data is not yet available.

Article Details

Section
Articles
Author Biographies

Ali Ahmad, Universitas Nusa Mandiri

Jurusan Ilmu Komputer, Magister Ilmu Komputer, Universitas Nusa Mandiri

Windu Gata, Universitas Nusa Mandiri

Jurusan Teknik Informatika, Fakultas Ilmu Komputer, Universitas Nusa Mandiri

References

CNN Indonesia, “Mengenal Sejarah Internet,” CNN INDONESIA, 2019. https://www.cnnindonesia.com/teknologi/20190312125646-185-376484/mengenal-sejarah-internet (accessed Jan. 16, 2021).

Gani, A.G., 2020. SEJARAH dan PERKEMBANGAN INTERNET DI INDONESIA. JURNAL MITRA MANAJEMEN, 5(2).

Damar, M., 2021. Metaverse Shape of Your Life for Future: A bibliometric snapshot. Journal of Metaverse, 1(1), pp.1-8.

Lee, L.H., Braud, T., Zhou, P., Wang, L., Xu, D., Lin, Z., Kumar, A., Bermejo, C. and Hui, P., 2021. All one needs to know about metaverse: A complete survey on technological singularity, virtual ecosystem, and research agenda. arXiv preprint arXiv:2110.05352.

Lee, J.Y., 2021. A study on metaverse hype for sustainable growth. International journal of advanced smart convergence, 10(3), pp.72-80.

Salsabila, U.H., Lestari, W.M., Habibah, R., Andaresta, O. and Yulianingsih, D., 2020. Pemanfaatan teknologi media pembelajaran di masa pandemi covid-19. Trapsila: Jurnal Pendidikan Dasar, 2(2), pp.1-13.

Fahmi Ahmad and Yuliawati, “Tren Kerja 2022, Makin Digital dan Fleksibel dengan Metaverse,” katadata.com. https://katadata.co.id/yuliawati/digital/61c99850ec00c/tren-kerja-2022-makin-digital-dan-fleksibel-dengan-metaverse (accessed Jan. 16, 2022).

C. Newton, “MARK IN THE METAVERSE,” www.theverge.com, 2021. https://www.theverge.com/22588022/mark-zuckerberg-facebook-ceo-metaverse-interview.

Jagokata.com, “Kamus Besar Bahasa Indonesia.” https://jagokata.com/arti-kata/.

Fang, X. and Zhan, J., 2015. Sentiment analysis using product review data. Journal of Big Data, 2(1), pp.1-14.

Risnawati, R., Budiman, I. and Arrahimi, A.R., 2019. Sentiment analysis svm dan svm-pso pada kolom komentar evaluasi dosen. Soliter, 2, pp.110-119.

Pamungkas, F.S. and Kharisudin, I., 2021, February. Analisis Sentimen dengan SVM, NAIVE BAYES dan KNN untuk Studi Tanggapan Masyarakat Indonesia Terhadap Pandemi Covid-19 pada Media Sosial Twitter. In PRISMA, Prosiding Seminar Nasional Matematika (Vol. 4, pp. 628-634).

Royan, S., Yulian, A. and Syaechurodji, S., 2021. IMPLEMENTASI DATA MINING MENGGUNAKAN METODE NAIVE BAYES DENGAN FEATURE SELECTION UNTUK PREDIKSI KELULUSAN MAHASISWA TEPAT WAKTU. Jurnal Ilmiah Sains Dan Teknologi, 5(2), pp.9-22.

Techvidvan, “SVM in R for Data Classification using e1071 Package,” https://techvidvan.com/t, 2022. https://techvidvan.com/tutorials/svm-in-r/ (accessed Jan. 17, 2022).

Irfani, F.F., Triyanto, M. and Hartanto, A.D., 2020. Analisis Sentimen Review Aplikasi Ruangguru Menggunakan Algoritma Support Vector Machine. JBMI (Jurnal Bisnis, Manajemen, dan Inform., vol. 16, no. 3, p. 258, 2020, doi: 10.26487/jbmi. v16i3. 8607.

Sihombing, R.E., Rachmatin, D. and Dahlan, J.A., 2019. Program Aplikasi Bahasa R Untuk Pengelompokan Objek Menggunakan Metode K-Medoids Clustering. Jurnal EurekaMatika, 7(1), pp.58-79.

Rintyarna, B.S., 2016. Sentiment Analysis pada Movie Review dengan Pendekatan Klasifikasi dalam Algoritma J. 48. JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia), 1(2).

R. Prakoso, “Positif and Negative Word,” 2020. https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/ (accessed Jan. 17, 2021).