Jurnal Riset Informatika
Vol. 3 No. 3 (2021): June 2021 Edition

SENTIMENT ANALYSIS OF TWITTER DATA ON DISTANCE LEARNING USING NAÏVE BAYES ALGORITHM

Putri Rana Khairina (Universitas Pancasila Jakarta)
Desti Fitriati (Universitas Pancasila Jakarta)



Article Info

Publish Date
30 Jun 2021

Abstract

Covid-19 is widespread, resulting in a global pandemic. Distance Learning System (DLS) is considered as a solution but, the reality of the implementation of DLS is not in accordance with the expectations of the community. Many twitter users wrote their opinions on DLS. The tendency of public sentiment can be used as a way to improve the existing education system in Indonesia and can be an input for the government in improving the DLS method that is being implemented. Thus, this study produced a system that can analyze tweet sentiment towards DLS. The tweet was obtained using the Twitter API. The method used is Naïve Bayes for the process of classification of positive, negative and neutral sentiments using 600 data. Then, data sharing is done 80% data training and 20% data testing that will be in the text preprocessing first. The accuracy of sentiment analysis of DLS using Naïve Bayes method using 3-fold Cross Validation produces an average of 93%.

Copyrights © 2021






Journal Info

Abbrev

jri

Publisher

Subject

Computer Science & IT

Description

Jurnal Riset Informatika, merupakan Jurnal yang diterbitkan oleh Kresnamedia Publisher. Jurnal Riset Informatika, berawal diperuntukan menampung paper-paper ilmiah yang dibuat oleh peneliti dan dosen-dosen program studi Sistem Informasi dan Teknik ...