Customer Complaints Clusterization of Government Drinking Water Company on Social Media Twitter using Text Mining

Ajeng Dewinta, Mohammad Isa Irawan

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

3 Citations (Scopus)

Abstract

Social media is considered one of the most effective platforms to communicate between companies and customers. Frequently, the customer of a product or service sends complaints via social media. Customers' complaint data serve as a good suggestion for companies and organizations to improve their products and services. With the increasing number of customer complaints that have entered through social media accounts, government-owned drinking water companies need a more efficient way to extract information from complaint data. In this research, text mining is used to extract information about customer complaints against drinking water companies from social media Twitter. Latent Dirichlet Allocation (LDA) and self-organizing maps (SOM) approach is applied to model complaint topics and find out which are most frequently complained the test results indicate grouping the data into five classes is the most appropriate model. Pipes leakage are the most frequently reported topics, 27.8% of total datasets.

Original languageEnglish
Title of host publication3rd 2021 East Indonesia Conference on Computer and Information Technology, EIConCIT 2021
EditorsRayner Alfred, Haviluddin Haviluddin, Aji Prasetya Wibawa, Joan Santoso, Fachrul Kurniawan, Hartarto Junaedi, Purnawansyah Purnawansyah, Endang Setyati, Herman Thuan To Saurik, Esther Irawati Setiawan, Eka Rahayu Setyaningsih, Edwin Pramana, Yosi Kristian, Kelvin Kelvin, Devi Dwi Purwanto, Eunike Kardinata, Prananda Anugrah
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages338-342
Number of pages5
ISBN (Electronic)9781665405140
DOIs
Publication statusPublished - 9 Apr 2021
Event3rd East Indonesia Conference on Computer and Information Technology, EIConCIT 2021 - Virtual, Surabaya, Indonesia
Duration: 9 Apr 202111 Apr 2021

Publication series

Name3rd 2021 East Indonesia Conference on Computer and Information Technology, EIConCIT 2021

Conference

Conference3rd East Indonesia Conference on Computer and Information Technology, EIConCIT 2021
Country/TerritoryIndonesia
CityVirtual, Surabaya
Period9/04/2111/04/21

Keywords

  • LDA
  • SOM
  • clustering
  • social media
  • text mining

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