SARI, ARMELIA LUVITA (2024) DIRECT MACHINE TRANSLATION PADA BAHASA LAMPUNG DIALEK API DAN NYO (STUDI KASUS : KANTOR BAHASA PROVINSI LAMPUNG). Strata 1 thesis, Universitas Teknokrat Indonesia.
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Abstract
The background of this research is the decline in the use of the Lampung language in the era of globalization and the inefficiency of manual dictionaries for translation. This research is limited to translating sentences based on the Lampung-Indonesian dictionary published in 2020 and the Lampung Api dictionary. The system developed is a Command Line Interface (CLI) using Python programming language, performing word-by-word translation. This study aims to develop an automatic translation machine based on Direct Machine Translation (DMT) capable of quickly translating text from the Lampung language dialects of Api and Nyo to Indonesian. The research methodology involves designing the system using the DMT paradigm, implementing the CLI-based translation program, and evaluating the translation quality using the BLEU Score. The results show that the translation machine produces varying accuracy: Api dialect achieves 64.24% accuracy, Nyo dialect 26.79%, and the combination of both dialects with the first dictionary achieves 59.92%. Using the second dictionary shows lower accuracy at 26.37%, indicating the vocabulary limitations in the database. This study contributes to the preservation of the Lampung language through translation technology relevant to local culture and provides a foundation for further development to improve translation accuracy.
| Item Type: | Thesis (Strata 1) |
|---|---|
| Uncontrolled Keywords: | Direct Machine Translation, Lampung Language, Api Dialect, Nyo Dialect, Automatic Translation, BLEU Score, Language Preservation. |
| Subjects: | INFORMATIKA > TJ Mechanical engineering and machinery |
| Divisions: | Fakultas Teknik dan Ilmu Komputer > S1 Informatika |
| Depositing User: | siswa pkl 4 |
| Date Deposited: | 27 Aug 2024 02:51 |
| Last Modified: | 09 Sep 2024 08:48 |
| URI: | http://repository.teknokrat.ac.id/id/eprint/6042 |
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