NAMED-ENTITY RECOGNITION PADA TEKS BERBAHASA INDONESIA MENGGUNAKAN METODE HIDDEN MARKOV MODEL DAN PART-OF-SPEECH TAGGING

SUFA, M. RIDHO PUTRA and Yusliani, Novi and Buchari, Muhammad Ali (2020) NAMED-ENTITY RECOGNITION PADA TEKS BERBAHASA INDONESIA MENGGUNAKAN METODE HIDDEN MARKOV MODEL DAN PART-OF-SPEECH TAGGING. Undergraduate thesis, Sriwijaya University.

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Abstract

Named-Entity Recognition (NER) is one of the research topics in the field of Natural Language Processing (NLP), it aims to provide Named-Entity labels that are refer to person's name, location name, organization name, and unit of time in the text. In this study, NER was conducted on Indonesian language text using Hidden Markov Model (HMM) method, and assisted by the Part-of-Speech Tagging process. The POS-Tagging process is applied to help HMM method in labeling Named-Entity labels on unknown words. Training data and test data used are data that has been developed by Fachri (2014) and (Syaifudin, 2016). The test was conducted on Indonesian language text with a total of 511 sentences. HMM and POS-Tagging method were successfully used to carry out the NER process, with performance level achieved based on average recall value is 83.82%, average precision value is 89.31%, and the average value of f-measure is 86.14%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Named-Entity Recognition
Subjects:	P Language and Literature > P Philology. Linguistics > P98-98.5 Computational linguistics. Natural language processing Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 7470 not found.
Date Deposited:	18 Aug 2020 07:19
Last Modified:	18 Aug 2020 07:19
URI:	http://repository.unsri.ac.id/id/eprint/33269

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