Application of text mining for classification of textual reports: A study of Indonesia's national complaint handling system

Isti Surjandari Prajitno, Chyntia Megawati, Arian Dhini, I. B.N. Sanditya Hardaya

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

5 Citations (Scopus)

Abstract

The rapid development of Information and Communication Technology (ICT) has made ICT an important part in the daily life of society. In that connection, the Indonesian government also tried to take advantage of ICT to be able to establish two-way communication with the public or commonly known as e-Government. One way is to create a website called LAPOR! (Layanan Aspirasi dan Pengaduan Online Rakyat or National Complaint Handling System). All kind of reports that conveyed by public through LAPOR! could be important inputs for the government to develop and improve public services. The high number of reports makes manual analysis becomes ineffective so that big data analysis becomes important. This study uses Text Mining methods for analyzing textual data in the form of opinions or complaints submitted by the public through LAPOR! by classifying those reports into classes. Then the data set in each class was clustered into specific topics. The results of this study show that the majority of public report is associated with poverty, particularly regarding social assistance, such as KPS (Kartu Perlindungan Sosial or Social Security Card) and BLSM (Bantuan Langsung Sementara Masyarakat or Temporary Direct Cash Assistance), which were not well distributed or not on target.

Original languageEnglish
Title of host publication6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016
PublisherIEOM Society
Pages1147-1156
Number of pages10
ISBN (Print)9780985549749
Publication statusPublished - 1 Jan 2016
Event6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016 - Kuala Lumpur, Malaysia
Duration: 8 Mar 201610 Mar 2016

Publication series

NameProceedings of the International Conference on Industrial Engineering and Operations Management
Volume8-10 March 2016
ISSN (Electronic)2169-8767

Conference

Conference6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016
Country/TerritoryMalaysia
CityKuala Lumpur
Period8/03/1610/03/16

Keywords

  • Classification
  • Clustering
  • Public's Reports
  • Self-Organizing Maps
  • Support Vector Machine
  • Text Mining

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