Twitter Sentiment Analysis of Indonesia Internet Service Provider: A Case Study of Indihome and Firstmedia

Adhitia Wiraguna, Prasetyo Komarodin, Indra Budi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Every company, especially internet service providers, needs to improve the quality of its products. The initial stage of improving product quality can be done by knowing customer satisfaction as an evaluation material. One way to determine customer satisfaction with a product is by calculating Customer Satisfaction using sentiment analysis on Twitter data, where Twitter is a very popular social media to get customer satisfaction feedback. The sentiment analysis method used is machine learning using a decision tree and random forest. From the two methods, the results show that the random forest method is better than the decision tree method. The oversampling method is also carried out to overcome the imbalanced class data set. The results of the Customer Satisfaction Score obtained show that tweets containing the word "Firstmedia"are better than tweets containing the word "Indihome"with a value of-41.67 for Firstmedia and-59.259

Original languageEnglish
Title of host publicationProceedings - 2nd International Conference on Computer Science and Engineering
Subtitle of host publicationThe Effects of the Digital World After Pandemic (EDWAP), IC2SE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665400459
DOIs
Publication statusPublished - 2021
Event2nd International Conference on Computer Science and Engineering, IC2SE 2021 - Padang, Indonesia
Duration: 16 Nov 202118 Nov 2021

Publication series

NameProceedings - 2nd International Conference on Computer Science and Engineering: The Effects of the Digital World After Pandemic (EDWAP), IC2SE 2021

Conference

Conference2nd International Conference on Computer Science and Engineering, IC2SE 2021
Country/TerritoryIndonesia
CityPadang
Period16/11/2118/11/21

Keywords

  • customer satisfaction score introduction
  • decision tree
  • random rorest
  • sentiment analysis

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