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Agus Harjoko
Magister Ilmu Komputer, Fakultas MIPA, Universitas Gadjah Mada, Yogyakarta
Computer Science & IT

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POS Tagging Bahasa Indonesia Dengan HMM dan Rule Based Kathryn Widhiyanti; Agus Harjoko
Jurnal Informatika Vol 8, No 2 (2012): Jurnal Informatika
Publisher : Universitas Kristen Duta Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (7275.517 KB) | DOI: 10.21460/inf.2012.82.125

Abstract

The research conduct a Part of Speech Tagging (POS-tagging) for text in Indonesian language, supporting another process in digitising natural language e.g. Indonesian language text parsing. POS-tagging is an automated process of labelling word classes for certain word in sentences (Jurafsky and Martin, 2000). The escalated issue is how to acquire an accurate word class labelling in sentence domain. The author would like to propose a method which combine Hidden Markov Model and Rule Based method. The expected outcome in this research is a better accurary in word class labelling, resulted by only using Hidden Markov Model. The labelling results –from Hidden Markov Model– are  refined by validating with certain rule, composed by the used corpus automatically. From the conducted research through some POST document, using Hidden Markov Model, produced 100% as the highest accurary for identical text within corpus. For different text within the referenced corpus, used words subjected in corpus, produced 92,2% for the highest accurary.
Co-Authors Kathryn Widhiyanti