The 1st International Conference on Computer Science and Engineering Technology Universitas Muria Kudus

Research Article

Review Sentiment Analysis of World Class Hotel Using Naive Bayes Classifier And Particle Swarm Optimization Method

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  • @INPROCEEDINGS{10.4108/eai.24-10-2018.2280546,
    author={Sopian Aji and Warjiyono Warjiyono and Dany Pratmanto and Angga Ardiansyah and Andrian Eko Widodo and Husni Faqih and Suleman Suleman and Fandhilah Fandhilah},
    title={Review Sentiment Analysis of World Class Hotel Using Naive Bayes Classifier And Particle Swarm Optimization Method},
    proceedings={The 1st International Conference on Computer Science and Engineering Technology Universitas Muria Kudus},
    publisher={EAI},
    proceedings_a={ICCSET},
    year={2018},
    month={11},
    keywords={sentiment analysis hotel review naive bayes classifier paticle swarm optimization},
    doi={10.4108/eai.24-10-2018.2280546}
}
  • Sopian Aji
    Warjiyono Warjiyono
    Dany Pratmanto
    Angga Ardiansyah
    Andrian Eko Widodo
    Husni Faqih
    Suleman Suleman
    Fandhilah Fandhilah
    Year: 2018
    Review Sentiment Analysis of World Class Hotel Using Naive Bayes Classifier And Particle Swarm Optimization Method
    ICCSET
    EAI
    DOI: 10.4108/eai.24-10-2018.2280546
Sopian Aji1,*, Warjiyono Warjiyono2, Dany Pratmanto2, Angga Ardiansyah2, Andrian Eko Widodo2, Husni Faqih2, Suleman Suleman2, Fandhilah Fandhilah2
  • 1: STMIK Nusa Mandiri Jakarta
  • 2: Universitas Bina Sarana Informatika
*Contact email: sopian.sop@bsi.ac.id

Abstract

Hotel service website is currently growing very rapidly, along with the development of tourism worldwide. The progress of world-class tourism is influenced by the provision of the international class accommodation. Selecting hotels considers generally expensive facilities, services and other supporting infrastructure. Currently the hotel booking service providers already provide facilities for tourists to write reviews and experiences of staying in the hotel room for other travel recommendations. With so many reviews displayed, it is necessary to perform a classification analysis of the review into a positive or negative grade. The method used for sentiment analysis of the hotel review is Naive Bayes Algorithm and Particle Swarm Optimization, This research examined data from sentiment hotel reviews on several hotel booking websites of 100 positive reviews and 100 negative reviews. The resulting combining Naive Bayes with Particle Swarm Optimization and obtains the best value with accuracy of 85.00%

Keywords
sentiment analysis hotel review naive bayes classifier paticle swarm optimization
Published
2018-11-29
Publisher
EAI
http://dx.doi.org/10.4108/eai.24-10-2018.2280546
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