MESIN PENTERJEMAH BAHASA INDONESIA-BAHASA SUNDA MENGGUNAKAN RECURRENT NEURAL NETWORKS
Abstract
Penterjemah merupakan suatu proses dimana suatu bahasa diubah ke dalam bahasa lain. Penterjemah pada Penelitian lalu dilakukan dengan menggunakan pendekatan Phrase-based Statistical Machine Translation (PSMT). Penelitian ini membangun sebuah penerjemah Bahasa Indonesia ke Bahasa Sunda. Adapun tahapan yang digunakan dimulai dari pra proses menggunakan text preprocessing dan word embedding Word2Vec dan pendekatan yang digunakan yaitu Neural Machine Translation (NMT) dengan arsitektur Encoder-Decoder yang didalamnya terdapat sebuah Recurrent Neural Network (RNN). Pengujian pada penelitian menghasilkan nilai optimal oleh GRU sebesar 99,17%. Model dengan menggunakan Attention mendapat 99.94%. Penggunaan model optimasi mendapat hasil optimal oleh Adam 99.35% dan hasil BLEU Score dengan optimal bleu 92.63% dan brievity penalty 0.929. Hasil dari mesin penterjemah menghasilkan prediksi pelatihan dari Bahasa Indonesia ke Bahasa Sunda apabila input kalimat sesuai dengan korpus dan hasil terjemahan kurang sesuai ketika input kalimat berbeda dari korpus.
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DOI: https://doi.org/10.33365/jti.v16i2.1930
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