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    Sentiment analysis system for movie review in Bahasa Indonesia using naive bayes classifier method

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    F. IK_Prosiding_Yanuar N_Sentiment analysis system.pdf (1.644Mb)
    Date
    2018-06-08
    Author
    Nurdiansyah, Yanuar
    Bukhori, Saiful
    Hidayat, Rahmad
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    Abstract
    There are many ways of implementing the use of sentiments often found in documents; one of which is the sentiments found on the product or service reviews. It is so important to be able to process and extract textual data from the documents. Therefore, we propose a system that is able to classify sentiments from review documents into two classes: positive sentiment and negative sentiment. We use Naive Bayes Classifier method in this document classification system that we build. We choose Movienthusiast, a movie reviews in Bahasa Indonesia website as the source of our review documents. From there, we were able to collect 1201 movie reviews: 783 positive reviews and 418 negative reviews that we use as the dataset for this machine learning classifier. The classifying accuracy yields an average of 88.37% from five times of accuracy measuring attempts using aforementioned dataset.
    URI
    http://repository.unej.ac.id/handle/123456789/85855
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    • LSP-Jurnal Ilmiah Dosen [7377]

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    Indonesia DSpace Group :

    University of Jember Repository
    IPB University Scientific Repository
    UIN Syarif Hidayatullah Institutional Repository