MESIN PENTERJEMAH BAHASA KOMERING BERBASIS MACHINE LEARNING DENGAN ALGORITMA MODEL ENCODER-DECODER

RAHMAWATI, TRI (2023) MESIN PENTERJEMAH BAHASA KOMERING BERBASIS MACHINE LEARNING DENGAN ALGORITMA MODEL ENCODER-DECODER. Diploma thesis, UNIVERSITAS BINA DARMA.

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Abstract

Regional language is one of the cultures that exist in Indonesia with a variety of regions throughout the archipelago. The Komering language is a local language spoken by the Komering tribe in South Sumatra province. The Komering language is used to speak in conveying daily words to the permanent residents of the Komering area. In fact, the Komering language in various villages has different types of speech delivery variations with different sounds and vocabulary, but the Komering language remains one family, namely the Komering language. The pronunciation of the Komering language is Ogan Komering Ilir, which is a permanent resident along the Komering river, covering Tanjung Lubuk sub-district and Kayu Agung city. To improve the preservation of this Komering regional language, this research needs to use a Machine Learing technology-based translator system media in order to help translate Komering language into Indonesian and vice versa. the existence of a Komering regional language translation machine that follows the development of the world of technology will make it easier to find out the translation of Komering language into Indonesian and vice versa. Therefore, the researchers used the Encoder-Decoder algorithm. The encoder-decoder algorithm is one of the machine learning architectures commonly used for machine translation. This algorithm is divided into two parts, the encoder serves to learn the input document and then process it into a translation for each Komering language word. Decoder serves to take the input data representation generated by the encoder and process it into translation results to Indonesian and vice versa. Keywords: Komering L

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