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PENGARUH POS TAGGING DENGAN METODE HMM PADA NER MENGGUNAKAN RULE BASED UNTUK ARTIKEL BERITA BAHASA INDONESIA

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Penilaian

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Nowadays the presentation of information can be easily found in various online media, one of them is article. The Article contains various information which is arranged in a very long writing and it takes a long time to find the information. One of the fields that can process hidden information in news articles is information extraction. The main task of information extraction is named entity recognition (NER). NER aims to identify and classify the words from the documents into some categories of named entity that have been set. In this study, NER was done in Indonesian news articles by using Rule Based to classify words into three classes of named-entity which are person, location, and organization. The rule regulations created based on contextual feature, morphology feature, and word class feature using post tagging with hidden markove model (HMM) method. This study will look at the performance result of NER system and the effect of POS tagging with HMM method againts word class feature of NER. The testing was done in 50 indonesian text news articles and the F-measure value was 62,55%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2007000029	T38095	T380952020	Central Library (REFERENSI)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T380952020

Publisher

Inderalaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2020

Collation

xix, VI-2 hlm, 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.

Content Type

Text

Media Type

other

Carrier Type

unspecified

Edition

-

Subject(s)

Teknik Informatika

Specific Detail Info

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Statement of Responsibility

NO

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