Sentiment Analysis of Standardization using Deep Belief Network: a case of Indonesian National Standards

Aries Agus Budi Hartanto, Zulkarnain, Isti Surjandari

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

Abstract

Free trade era requires increasing the competitiveness of local products in the global market, through standardization. The standardization policy is including how to plan, formulate, establish, implement, enforce, maintain, and supervise National Standard, e.g Indonesian National Standard called SNI. SNI is useful in order to create competitiveness and consumer protection. The consistency of standardization shows through standardization activity, that requires time and high resources. The number of SNI and the breadth of products distribution cannot be monitor simultaneously in the same years, also another obstacle in standardization activities. Therefore the aim of this study is to find a classification of standardization activity, which to becomes an important part of evaluation policy. The development of media plays a role in policy making, information and opinions from the media can change standardization's policy strategies. The contribution of this research is using text mining from standardization publication in media, to find useful knowledge. It's useful to build an input alternative, in the form of media sentiment analysis in standardization activity, that has never been done before. It gives an agile method for dealing with rapid changes in the standardization process. This study uses a deep belief network (DBN) method for the classification of media sentiment. Besides using DBN, this study also compares DBN with other classification methods, namely Naive Bayes (NB) and Support Vector Machine (SVM). These research results show the accuracy of the classification model with DBN reaches 77%, NB reaches 74% and SVM reaches 77%. Moreover, the results show that the most negative sentiment is 19% and the most positive sentiment is 29.20%. Both of the sentiments are the member of class about implementation and the mandatory regulation of SNI, and those aspects becoming media concentration. Standardization situation is expected to be captured as the output of this study so that it can contribute to improving the standardization policy in Indonesia.

Original languageEnglish
Title of host publicationProceedings of the 4th Asia Pacific Conference on Research in Industrial and Systems Engineering
Subtitle of host publicationBuilding Business Resilience to Face the Challenge in Pandemic Era, APCORISE 2021
PublisherAssociation for Computing Machinery
Pages621-626
Number of pages6
ISBN (Electronic)9781450390385
DOIs
Publication statusPublished - 25 May 2021
Event4th Asia Pacific Conference on Research in Industrial and Systems Engineering: Building Business Resilience to Face the Challenge in Pandemic Era, APCORISE 2021 - Depok, Indonesia
Duration: 25 May 2021 → …

Publication series

NameACM International Conference Proceeding Series

Conference

Conference4th Asia Pacific Conference on Research in Industrial and Systems Engineering: Building Business Resilience to Face the Challenge in Pandemic Era, APCORISE 2021
Country/TerritoryIndonesia
CityDepok
Period25/05/21 → …

Keywords

  • Deep belief network
  • Sentiment analysis
  • Standardization
  • Text mining

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