ANALISIS SENTIMEN TERHADAP DAMPAK PERANG ISRAEL - PALESTINA MELALUI DATA TWITTER MENGGUNAKAN NAIVE BAYES

Alfian Noer Halim; Saruni Dwiasnati

doi:10.22441/format.2024.v13.i2.010

ANALISIS SENTIMEN TERHADAP DAMPAK PERANG ISRAEL - PALESTINA MELALUI DATA TWITTER MENGGUNAKAN NAIVE BAYES

Alfian Noer Halim, Saruni Dwiasnati

Abstract

The increasing development of information technology makes it easy for people to get various information only through social media such as Twitter. Twitter is a mainstay social networking application and source of information on world events. With Twitter, people can get a lot of the latest news. One piece of information that is widely discussed and is a trending topic on Twitter is the impact of the Israeli and Palestinian war. It is important to analyze the feelings of the impact of the ceasefire between Israel and Palestine from the amount of information in online media. The data used is Twitter, a social media platform. This research was conducted to analyze people's reactions to data in the form of tweets and group them according to the Naïve Bayes method into positive, neutral or negative opinions. In implementing the Naïve Bayes algorithm which uses 3 models of the Naïve Bayes algorithm, namely Gaussian, Multinomial, and Bernoulli, it shows different results, namely 50% for the Naïve Bayes Gaussian model, 57% for the Naïve Bayes Bernoulli model, and Naïve Bayes Multinomial model is 65 %. This shows that the Multinomial Naïve Bayes model is better than other models in classifying the data in this case.

Keywords

Naïve Bayes; Gaussian; Multinomial; Bernoulli

Full Text:

PDF

References

Irsyad H, & Taqwiym, A. (2021). Sentimen Analisis Masyarakat Terhadap Rakyat Palestina dengan Klasifikasi Naive Bayes. Jurnal Sistem Telekomunikasi Elektronika Sistem Kontrol Power Sistem & Komputer, Vol. 1 / No. 2. 167-168

Astari, N., Divayana, D., & Indrawan, G. (2020).Analisis Sentimen Dokumen Twitter Mengenai Dampak Virus Corona Menggunakan Metode Naive Bayes Classifier. JURNAL SISTEM DAN INFORMATIKA (JSI), 23.

Salsabila, (2022). ANALISIS SENTIMEN PADA MEDIA SOSIAL TWITTER TERHADAP TOKOH GUS DUR MENGGUNAKAN METODE NAÏVE BAYES DAN SUPPORT VECTOR MACHINE (SVM) . 4.

Ahmad Rifai, “ANALISIS SENTIMEN OPINI MASYARAKAT TENTANG PENYAKIT HEPATITIS AKUT MENGGUNAKAN METODE NAÏVE BAYES,” J. RESTI, vol. 6, p. 22, 2022.

Sukamto, & Shalahuddin, M. (2013). Rekayasa Perangkat Lunak Terstruktur Dan Berorientasi Objek. Bandung: Informatika, 1-9.

Derajad Wijaya, H., & Dwiasnati, S. (2020). Implementasi Data Mining dengan Algoritma Naïve Bayes pada Penjualan Obat. JURNAL INFORMATIKA, 7(1). http://ejournal.bsi.ac.id/ejurnal/index.php/ji.

Dwianto, E., & Sadikin, M. (n.d.). Analisis Sentimen Transportasi Online pada Twitter Menggunakan Metode Klasifikasi Naïve Bayes dan Support Vector Machine.

Khoirul, M., Hayati, U., & Nurdiawan, O. (2023). ANALISIS SENTIMEN APLIKASI BRIMO PADA ULASAN PENGGUNA DI GOOGLE PLAY MENGGUNAKAN ALGORITMA NAIVE BAYES. In Jurnal Mahasiswa Teknik Informatika (Vol. 7, Issue 1).

Miftahusalam, A., Febby Nuraini, A., Khoirunisa, A. A., & Pratiwi, H. (n.d.). Perbandingan Algoritma Random Forest, Naïve Bayes, dan Support Vector Machine Pada Analisis Sentimen Twitter Mengenai Opini Masyarakat Terhadap Penghapusan Tenaga Honorer.

Naufal, M. F., Arifin, T., & Wirjawan, H. (n.d.). Analisis Perbandingan Tingkat Performa Algoritma SVM, Random Forest, dan Naïve Bayes untuk Klasifikasi Cyberbullying pada Media Sosial. 8, 82. https://tunasbangsa.ac.id/ejurnal/index.php/jurasik

Ruger, A. H., Suyanto, M., & Kurniawan, M. P. (2021). Sentimen Analisis Pelanggan Shopee di Twitter dengan Algoritma Naive Bayes. Journal of Information Technology, 1(2), 26-29.

Tanggraeni, A. I., & Sitokdana, M. N. (2022). Analisis Sentimen Aplikasi EGovernment Pada Google Play Menggunakan Algoritma Naïve Bayes. JATISI (Jurnal Teknik Informatika dan Sistem Informasi), 9(2), 785-795.

Das, S., Bhattacharyya, K., & Sarkar, S. (2023). Performance Analysis of Logistic Regression, Naive Bayes, KNN, Decision Tree, Random Forest and SVM on Hate Speech Detection from Twitter. International Research Journal of Innovations in Engineering and Technology (IRJIET), 7(3), 24–28. https://doi.org/10.47001/IRJIET/2023.703004

Duei Putri, D., Nama, G. F., & Sulistiono, W. E. (2022). Analisis Sentimen Kinerja Dewan Perwakilan Rakyat (DPR) Pada Twitter Menggunakan Metode Naive Bayes Classifier. Jurnal Informatika Dan Teknik Elektro Terapan, 10(1). https://doi.org/10.23960/jitet.v10i1.2262.

DOI: http://dx.doi.org/10.22441/format.2024.v13.i2.010

Refbacks

There are currently no refbacks.

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

Format : Jurnal Ilmiah Teknik Informatika
Fakultas Ilmu Komputer Universitas Mercu Buana
Jl. Raya Meruya Selatan, Kembangan, Jakarta 11650
Tlp./Fax: +62215840816
http://publikasi.mercubuana.ac.id/index.php/format