Abstract
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.
Publisher
Universitas Nusantara PGRI Kediri
Reference22 articles.
1. F. Ariyani, “Distribusi Verba Berfrefiks (N-) Pada Bahasa Lampung dalam Kitab Kuntara Raja Niti dan Buku Ajar. Ranah: Jurnal Kajian Bahasa 3,” Ranah J. Kaji. Bhs., vol. 3, no. 2, pp. 124–134, 2014, doi: https://doi.org/10.26499/rnh.v3i2.43.
2. P. Bhattacharyya, Machine Translation. Boca Raton: Taylor & Francis Group, 2015.
3. Z. Abidin, “Penerapan Neural Machine Translation untuk Eksperimen Penerjemahan secara Otomatis pada Bahasa Lampung – Indonesia,” Pros. Semin. Nas. Metod. Kuantitatif 2017, no. 978, pp. 53–68, 2017.
4. Z. Abidin, A. Sucipto, and A. Budiman, “Penerjemahan Kalimat Bahasa Lampung-Indonesia Dengan Pendekatan Neural Machine Translation Berbasis Attention Translation of Sentence Lampung-Indonesian Languages With Neural Machine Translation Attention Based,” J. Kelitbangan, vol. 06, no. 02, pp. 191–206, 2018.
5. P. Permata and Z. Abidin, “Statistical Machine Translation Pada Bahasa Lampung Dialek Api Ke Bahasa Indonesia,” Media Inform. Budidarma, vol. 4, no. 3, pp. 519–528, 2020, doi: 10.30865/mib.v4i3.2116.
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