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CLASSIFICATION OF EMOTIONS IN INDONESIAN TEXTS USING K-NN METHOD

-, Arifin and Purnama, Ketut Eddy (2014) CLASSIFICATION OF EMOTIONS IN INDONESIAN TEXTS USING K-NN METHOD. Jurnal Informatika.

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    Abstract

    This paper aims to classify texts in Indonesian language into emotion expression classes. The data were taken from 6 basic emotion classes whose training documents and test documents were obtained from articles in www.kompas.com, www.suaramerdeka.com, and www.detik.com. The text weighing was processed by using TFID method which is an integration of Term Frequency (TF) and Inverse Document Frequency (IDF). In the classification process, K-Nearest Neighbor (K-NN) was used to see how far this method could classify emotion expression of Indonesian language. The test shows that the classification of the Indonesian texts for the six basic emotion classes by using K-NN method results in accurateness percentage of 71.26%, obtained at k=40 as the optimum value. Keywords: basic emotions, K-Nearest Neighbor, Indonesian language, TFIDF

    Item Type: Article
    Subjects: T Technology > Teknik Informatika > INF Informatika
    Universitas Dian Nuswantoro > Fakultas Ilmu Komputer > Teknik Informatika > INF Informatika
    Semantik 2013 > INF Informatika
    Divisions: Library of Congress Subject Areas > T Technology > Teknik Informatika > INF Informatika
    Fakultas Ilmu Komputer > Teknik Informatika > INF Informatika
    Semantik 2013 > INF Informatika
    Depositing User: Psi Udinus
    Date Deposited: 16 Dec 2014 11:12
    Last Modified: 16 Dec 2014 11:14
    URI: http://eprints.dinus.ac.id/id/eprint/14094

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