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ITS » Paper and Presentation » S2 Teknik Informatika
Posted by tondoindra@gmail.com at 22/10/2014 16:50:52  •  1360 Views


TERM WEIGHTING BERBASIS INDEKS BUKU DAN KELAS UNTUK PERANGKINGAN DOKUMEN BERBAHASA ARAB

TERM WEIGHTING BASED ON BOOK AND CLASS INDICES FOR ARABIC DOCUMENT RANKING

Author :
M. ALI FAUZI ( 5111201036 )




ABSTRAK

Information Retrieval berdasarkan query tertentu sudah jamak ditemukan pada sistem komputer saat ini. Salah satu metode yang populer digunakan adalah perangkingan dokumen menggunakan space vector model berbasis pada nilai term weighting TF.IDF. Pada penelitian ini terdapat beberapa buku berbahasa Arab yang memiliki puluhan bahkan ratusan halaman. Masing-masing halaman dari buku tersebut adalah sebuah dokumen yang akan diranking berdasarkan query dari pengguna. TF.IDF hanya melakukan pembobotan berbasis pada dokumen tanpa memperhatikan indeks buku dan kelas yang merupakan induk dokumen tersebut sehingga kinerjanya kurang maksimal jika diimplementasikan pada kasus ini. Oleh karena itu diusulkan metode baru term weighting yang berbasis pada indeks buku dan kelas. Metode ini memperhatikan frekuensi kemunculan term pada keseluruhan buku dan kelas. Metode yang disebut inverse class frequency ICF dan inverse book frequency IBF ini digabungkan dengan metode sebelumnya sehingga menjadi TF.IDF.ICF.IBF. Pengujian metode ini menggunakan dataset dari beberapa e-book berbahasa arab. Hasil penelitian menunjukkan bahwa metode yang diajukan terbukti dapat diaplikasikan pada perangkingan dokumen berbahasa arab dan memiliki performa yang lebih bagus dibanding metode sebelumnya dengan nilai F-Measure 75 precision 76 dan recall mencapai 74.


ABSTRACT

Information Retrieval based on specific queries is common to the current computer systems. One of the popular methods used is the document ranking method using vector space models based on TF.IDF term weighting. In this study there are several books in Arabic that has tens or even hundreds of pages. Each page of the book is a single document that will be ranked based on the user query. TF.IDF only perfoms term weighting based on the document without regard to the indexes of the book and class of the document. Therefore a new method of term weighting that based on books and classes indexes proposed. This method favor the frequency of term in whole books and classes. This method that called inverse class frequency ICF and inverse book frequency IBF then combined with the previous method so that it becomes TF.IDF.ICF.IBF. This new method was tested using a dataset from some Arabic e-books. The experimental results show that the proposed method can be implemented on document ranking method and the performances are better than some previous methods with F-Measure value 75 precision value 76 dan recall value 74.



KeywordsPerankingan Dokumen; Term Weighting; TF.IDF; ICF; IBF; Indeks Buku; Indeks Kelas
 
Subject:  Sistem penyimpanan dan temu kembali informasi
Contributor
  1. Dr. Agus Zainal Arifin, S.Kom, M.Kom
  2. Anny Yuniarti, S.Kom, M.Comp.Sc
Date Create: 16/08/2013
Type: Text
Format: PDF
Language: Indonesian
Identifier: ITS-paper-51021140005466
Collection ID: 51021140005466
Call Number: RTIf 025.524 Fau t


Source
Paper And Presentation of Informatics Engineering RTIf 025.524 Fau t, 2014

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Copyright @2013 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




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