Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal IJISTECH (International Journal Of Information System & Technology) IJISTECH
Rima Tamara Aldisa
Faculty of Communication and Information Technology, Universitas Nasional
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Sentiment Analysis of Public Transportation Services on Twitter Social Media Using the Method Naïve Bayes Classifier Rima Tamara Aldisa; Pandu Maulana; Muhammad Aldinugroho
IJISTECH (International Journal of Information System and Technology) Vol 5, No 4 (2021): December
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v5i4.166

Abstract

Public transportation services in Indonesia, especially Jabodetabek, have used social media, especially Twitter, as a way to improve services. Currently, the use of online transportation services is like a need; it is necessary to conduct a sentiment analysis of online transportation to find out how people respond to these online transportation services. This research was made to analyze community responses with data analysis in the form of tweets that filtered with a public transportation-related keyword then classified into positive and negative classes using the Naïve Bayes Classifier method. Based on the system built, the total sentiment results for the percentage of the occurrence of positive words were 0.507843137, and the sentiment results for the percentage of negative word occurrences were 1.4132493. The results show that the level of negative sentiment from public tweets is greater than the level of positive sentiment.
Sentiment Analysis of Public Transportation Services on Twitter Social Media Using the Method Naïve Bayes Classifier Rima Tamara Aldisa; Pandu Maulana; Muhammad Aldinugroho
IJISTECH (International Journal of Information System and Technology) Vol 5, No 4 (2021): December
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (818.822 KB) | DOI: 10.30645/ijistech.v5i4.166

Abstract

Public transportation services in Indonesia, especially Jabodetabek, have used social media, especially Twitter, as a way to improve services. Currently, the use of online transportation services is like a need; it is necessary to conduct a sentiment analysis of online transportation to find out how people respond to these online transportation services. This research was made to analyze community responses with data analysis in the form of tweets that filtered with a public transportation-related keyword then classified into positive and negative classes using the Naïve Bayes Classifier method. Based on the system built, the total sentiment results for the percentage of the occurrence of positive words were 0.507843137, and the sentiment results for the percentage of negative word occurrences were 1.4132493. The results show that the level of negative sentiment from public tweets is greater than the level of positive sentiment.
Co-Authors Muhammad Aldinugroho Pandu Maulana