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

ZULKARNAIN, ADE LISMITA and Yusliani, Novi and Rodiah, Desty (2020) PENGARUH POS TAGGING DENGAN METODE HMM PADA NER MENGGUNAKAN RULE BASED UNTUK ARTIKEL BERITA BAHASA INDONESIA. Undergraduate thesis, Sriwijaya University.

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Abstract

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%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Named Entity Recognition, Rule Based, POS Tagging with Hidden Markove Model
Subjects:	R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 9072 not found.
Date Deposited:	01 Dec 2020 01:41
Last Modified:	01 Dec 2020 03:47
URI:	http://repository.unsri.ac.id/id/eprint/38095

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