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ITS » Master Theses » Jaringan Cerdas Multimedia S2
Posted by hassane@its.ac.id at 26/05/2010 14:46:25  •  3041 Views


KLASIFIKASI EMOSI UNTUK TEKS BAHASA INDONESIA MENGGUNAKAN METODE NAIVE BAYES

EMOTION CLASSIFICATION FOR INDONESIAN TEXT USING NAIVE BAYES METHOD

Author :
DESTUARDI, I.  ( 2207205717 )




ABSTRAK

Komunikasi dapat dilakukan dari informasi verbal dan non-verbal verbal dapat berupa tulisan yang diperoleh dari kata kalimat paragraf dan sebagainya untuk penggalian informasi teksnya menggunakan klasifikasi teks. Pada proses klasifikasi itu akan digunakan data set yang telah diketahui kelas emosinya yaitu jijik malu marah sedih senang dan takut dengan menggunakan metode Nave Bayes dan Multinomial Nave Bayes. Akan dilihat sejauh mana kedua metode itu dapat mengklasifikasikan data emosi berbahasa indonesia. Hasil percobaan menunjukkan dengan metode Multinomial Naive Bayes mampu mengenali dokumen dengan tingkat akurasi 61.57 dengan rasio data 0.6 dengan melakukan perlakuan berbeda pada preprosessing data


ABSTRACT

Communication can be done from verbal information and non-verbal verbal can be obtained by writing the words sentences paragraphs and so on for extracting the text information using text classification. In the classification process will be used the data sets of known classes of emotion disgust shame anger sadness joy and fear by using Naive Bayes and Multinomial Naive Bayes. Will be seen the extent to which the two methods that can classify the emotion data of Indonesian language. The results show the method Multinomial Naive Bayes is able to identify documents with 61.57 accuracy rate with a ratio of 0.6 by performing the data differently to treatment data preprosessing



Keywordsklasifikasi teks; emosi; model multinomial; na´ve bayes
 
Subject:  Analisis Cluster - Program Komputer
Contributor
  1. Moch. Hariadi, ST., MSc., PhD
Date Create: 16/02/2010
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-Master-3100010039214
Collection ID: 3100010039214
Call Number: RTE 003.74 Des k


Source
Master Theses, Electrical Engineering, RTE 003.74 Des k, 2009

Coverage
ITS Community

Rights
Copyright @2010 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




[ Download - Open Access ]

  1.  ITS-Master-10508-Abstract_id.pdf - 76 KB
  2.  ITS-Master-10508-Abstract_en.pdf - 76 KB
  3.  ITS-Master-10508-Conclusion.pdf - 51 KB
  4.  ITS-Master-10508-Paper.pdf - 151 KB




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