Translation of the Lampung Language Text Dialect of Nyo into the Indonesian Language with DMT and SMT Approach
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi
View Publication Info| Field | Value | |
| Title |
Translation of the Lampung Language Text Dialect of Nyo into the Indonesian Language with DMT and SMT Approach
Translation of the Lampung Language Text Dialect of Nyo into the Indonesian Language with DMT and SMT Approach |
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| Creator |
Abidin, Zaenal
Permata, Permata Ariyani, Farida |
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| Subject |
Lampung language dialect of Nyo
Direct machine translation Statistical machine translation Bilingual Evaluation Understudy Lampung language dialect of Nyo Direct machine translation Statistical machine translation Bilingual Evaluation Understudy |
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| Description |
Research on the translation of Lampung language text dialect of Nyo into Indonesian is done with two approaches, namely Direct Machine Translation (DMT) and Statistical Machine Translation (SMT). This research experiment was conducted as a preliminary effort in helping students immigrants in the province of Lampung, translating the Lampung language dialect of Nyo through prototypes or models was built. In the DMT approach, the dictionary is used as the primary tool. In contrast, in SMT, the parallel corpus of Lampung Nyo and Indonesian language is used to make language models and translation models using Moses Decoder. The result of text translation accuracy with the DMT approach is 39.32%, and for the SMT approach is 59.85%. Both approaches use Bilingual Evaluation Understudy (BLEU) assessment.
Research on the translation of Lampung language text dialect of Nyo into Indonesian is done with two approaches, namely Direct Machine Translation (DMT) and Statistical Machine Translation (SMT). This research experiment was conducted as a preliminary effort in helping students immigrants in the province of Lampung, translating the Lampung language dialect of Nyo through prototypes or models was built. In the DMT approach, the dictionary is used as the primary tool. In contrast, in SMT, the parallel corpus of Lampung Nyo and Indonesian language is used to make language models and translation models using Moses Decoder. The result of text translation accuracy with the DMT approach is 39.32%, and for the SMT approach is 59.85%. Both approaches use Bilingual Evaluation Understudy (BLEU) assessment. |
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| Publisher |
Universitas Nusantara PGRI Kediri
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| Date |
2021-02-01
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion |
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| Format |
application/pdf
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| Identifier |
https://ojs.unpkediri.ac.id/index.php/intensif/article/view/14670
10.29407/intensif.v5i1.14670 |
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| Source |
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi; Vol. 5 No. 1 (2021): February 2021; 58-71
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi; Vol 5 No 1 (2021): February 2021; 58-71 2549-6824 2580-409X |
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| Language |
eng
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| Relation |
https://ojs.unpkediri.ac.id/index.php/intensif/article/view/14670/1966
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| Rights |
Copyright (c) 2021 INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi
https://creativecommons.org/licenses/by-sa/4.0 |
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