Analisis perbandingan sentimen Corona Virus Disease-2019 (Covid19) pada Twitter Menggunakan Metode Logistic Regression Dan Support Vector Machine (SVM)

Kelvin Kelvin; Jepri  Banjarnahor; Evta Indra -; Marlince NK Nababan; Stiven Hamonangan Sinurat

doi:10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2365

pdf

Published: Feb 8, 2022

DOI: https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2365

Keywords:

Sentimen, NLP, Logistic Regression, Support Vector Machine (SVM)

Kelvin Kelvin

Jepri Banjarnahor

Evta Indra -

Marlince NK Nababan

UNIVERSITAS PRIMA INDONESIA

Stiven Hamonangan Sinurat

Program Studi Sistem Informasi, Fakultas Teknologi dan Ilmu Komputer, Universitas Prima Indonesia

Abstract

Melihat perkembangan twitter tersebut maka twitter menjadi salah satu media yang dapat digunakan untuk melakukan analisis sentimen terhadap bebagai topik. Penelitian ini melakukan suatu analisis sentimen terhadap bahasan yang saat ini sering menjadi trending topic di twitter yaitu “CoronaVirus Disease-2019 (covid19)”. Penyebaran virus ini juga langsung dibicarakan oleh banyak kalangan masyarakat twitter, saat ini virus corona tengah menjadi perhatian dunia internasional. Banyaknya jumlah angka korban dan cepatnya penularan virus membuat masyarakat khawatir dan muncul berbagai opini tentang virus corona, Opini inilah yang kemudian di analisa untuk diketahui polaritasnya dengan analisis sentimen. Metode yang digunakan adalah Logistic Regression dan Support Vector Machine (SVM) dimana SVM memiliki nilai akurasi 91,15% dalam data test sedangkan metode Logistic Regression mendapatkan nilai akurasi sebanyak 87,68% dalam data test.

How to Cite

[1]

K. Kelvin, J. . Banjarnahor, E. I. -, M. NK Nababan, and S. H. Sinurat, “Analisis perbandingan sentimen Corona Virus Disease-2019 (Covid19) pada Twitter Menggunakan Metode Logistic Regression Dan Support Vector Machine (SVM)”, JUSIKOM PRIMA, vol. 5, no. 2, pp. 47 - 52, Feb. 2022.

Issue

Vol. 5 No. 2 (2022): Jurnal Sistem Informasi dan Ilmu Komputer Prima (JUSIKOM Prima)

Section

Articles

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

Authors who publish their manuscripts through the Journal of Information Systems and Computer Science agree to the following:

Copyright to the manuscripts of scientific papers in this Journal is held by the author.
The author surrenders the rights when first publishing the manuscript of his scientific work and simultaneously the author grants permission / license by referring to the Creative Commons Attribution-ShareAlike 4.0 International License to other parties to distribute his scientific work while still giving credit to the author and the Journal of Information Systems and Computer Science as the first publication medium for the work.
Matters relating to the non-exclusivity of the distribution of the Journal that publishes the author's scientific work can be agreed separately (for example: requests to place the work in the library of an institution or publish it as a book) with the author as one of the parties to the agreement and with credit to sJournal of Information Systems and Computer Science as the first publication medium for the work in question.
Authors can and are expected to publish their work online (e.g. in a Repository or on their Organization's/Institution's website) before and during the manuscript submission process, as such efforts can increase citation exchange earlier and with a wider scope.