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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology)
Alvian Burhanuddin
Universitas Islam Negeri Maulana Malik Ibrahim Malang
Computer Science & IT

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Phrase Based and Neural Network Translation for Text Transliteration from Arabic to Indonesia Alvian Burhanuddin; Ahmad Latif Qosim; Rizqi Amaliya
MATICS Vol 14, No 1 (2022): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v14i1.13853

Abstract

Abstract- Transliteration is one solution to overcome the inability to read and write Arabic in Indonesia. However, this transliteration has many different versions in reality. The many differences in transliteration versions make it difficult for people to understand and pronounce the Arabic sentence. So there needs to be an approach to overcome the problem of these differences. The data mining approach can be used as an option to reduce these differences. In this study, the researcher found that automatic transliteration based on the data mining model had a reasonably good BLEU value.
Co-Authors Ahmad Latif Qosim Rizqi Amaliya