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SENTIMENT ANALYSIS OF WEST POP MUSIC BASED ON COMMENTS IN YOUTUBE USING NAIVE BAYES CLASSIFIER

MUHAMMAD, M HERLAMBANG (2017) SENTIMENT ANALYSIS OF WEST POP MUSIC BASED ON COMMENTS IN YOUTUBE USING NAIVE BAYES CLASSIFIER. Skripsi,Fakultas Ilmu Komputer.

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    Abstract

    Music world in Indonesia now is growing. proved from the increasing number of new musicians in Indonesia. A large number of musicians will certainly be proportional to the number of music listeners. But unfortunately, with the large number of song creation of new musicians is not matched by the quality of the song. Many of the songs are more advanced aspects of entertainment without thinking about the quality of the song. Sentiment analysis or opinion mining is the computational study of the opinions of people, sentiments and emotions through entities and attributes that we have expressed in the form of text. Sentiment analysis will group the polarity of the existing text in a sentence or document to find out the opinions expressed in the sentence or whether the documents are either positive, negative or neutral. This study will produce the percentage about positive and negative comment in YouTube and make recommended music using Naive Bayes Classifier method. if the percentage of negative comments is higher than the percentage of positive comments the system will not recommend the music but if the percentage of positive comments is higher than the percentage of negative comments the system will recommend that music.

    Item Type: Article
    Subjects: T Technology > Teknik Informatika
    Universitas Dian Nuswantoro > Fakultas Ilmu Komputer > Teknik Informatika
    Divisions: Fakultas Ilmu Komputer
    Depositing User: Psi Udinus
    Date Deposited: 04 May 2017 16:01
    Last Modified: 04 May 2017 16:01
    URI: http://eprints.dinus.ac.id/id/eprint/22266

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