Authors:

I Gde Made Hendra Pradiptha, Ngurah Agus Sanjaya ER

Abstract:

“Part-of-Speech tagging or word class labeling is a process for labeling a word class in a word in a sentence. Previous research on POS Tagger, especially for Indonesian, has been done using various approaches and obtained high accuracy values. However, not many researchers have built POS Tagger for Balinese. In this article, we are interested in building a POS Tagger for Balinese using a probabilistic approach, specifically the Hidden Markov Model (HMM). HMM is selected to deal with ambiguity since it gives higher accuracy and fast processing time. We used k-fold cross-validation (with k = 10) and tagged corpus around 3669 tokens with 21 tags. Based on the experiments conducted, the HMM method obtained an accuracy of 68.56%.”

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PDF:

https://jurnal.harianregional.com/jlk/full-64491

Published

2020-11-24

How To Cite

PRADIPTHA, I Gde Made Hendra; SANJAYA ER, Ngurah Agus. Building Balinese Part-of-Speech Tagger Using Hidden Markov Model (HMM).JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 9, n. 2, p. 303-308, nov. 2020. ISSN 2654-5101. Available at: https://ojs.unud.ac.id/index.php/JLK/article/view/64491. Date accessed: 08 Jul. 2024. doi:https://doi.org/10.24843/JLK.2020.v09.i02.p18.

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Issue

Vol 9 No 2 (2020): JELIKU Volume 9 No 2, November 2020

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License