Comparison of Translation Techniques by Google Translate and U-Dictionary: How Differently Does Both Machine Translation Tools Perform in Translating?

Kammer Tuahman Sipayung; Novdin Manoktong Sianturi; I Made Dwipa Arta; Yeti Rohayati; Diani Indah

doi:10.31849/elsya.v3i3.7517

Kammer Tuahman Sipayung Universitas HKBP Nommensen, Medan, Indonesia https://orcid.org/0000-0002-4839-2475
Novdin Manoktong Sianturi Universitas Simalungun, Pematangsiantar, Indonesia https://orcid.org/0000-0001-5572-4063
I Made Dwipa Arta Udayana University, Denpasar, Indonesia https://orcid.org/0000-0001-8512-0586
Yeti Rohayati Universitas Langlangbuana, Bandung, Indonesia
Diani Indah Universitas Langlangbuana, Bandung, Indonesia

DOI: https://doi.org/10.31849/elsya.v3i3.7517

Keywords: Machine Translation, Computational Linguistics, Translation Techniques, Expository Text, Google Translate, U-dictionary

Abstract

Better translation produced by computation linguistics should be evaluated through linguistics theory. This research aims to describe translation techniques between Google Translate and U-Dictionary. The study used a qualitative research method with a descriptive design. This design was used to describe the occurrences of translation techniques in both translation machine, with the researchers serving as an instrument to compare translation techniques which is produced on machine. The data are from expository text entitled “Importance of Good Manners in Every Day Life”. The total data are 122 words/phrases which are pairs of translations, English as source language and Indonesia as target language. The result shows that Google Translate apply five of Molina & Albir’s (2002) eighteen translation techniques, while U-dictionary apply seven techniques. Google Translate dominantly apply literal translation techniques (86,8%) followed by reduction translation techniques (4,9%). U-dictionary also dominantly apply literal translation techniques (75,4%), but follows with the variation translation techniques (13,1%). This study showed that both machines produced different target texts for the same source language due to different applications of techniques, with U-dictionary proven to apply more variety of translation techniques than Google Translate. The researcher hopes this study can be used as an evaluation for improving the performance of machine translations.

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Author Biographies

Kammer Tuahman Sipayung, Universitas HKBP Nommensen, Medan, Indonesia

Kammer Tuahman Sipayung is a lecturer at English language education department at University of HKBP Nommensen Medan. He completed his Doctoral program from Universitas Sumatra Utara at Linguistic Department (2015-2018). He received the BPDN (Beasiswa Pascasarjana Dalam Negeri) scholarship from the government of Indonesia to fulfil his interest in linguistics studies centred on translation. He has a great desire to conduct a multidisciplinary research drawing on linguistics and educational theories on English language. By 2021, his writing has been published on several international journals, proceedings and accredited journal (S2 up to S6).

Novdin Manoktong Sianturi, Universitas Simalungun, Pematangsiantar, Indonesia

Novdin M. Sianturi was born in 2009. He joined as a Teaching Honorary Staff in the Civil Engineering Study Program and was promoted as a permanent teaching staff in 2010 with notable expertise in construction management, soil mechanics and water building irrigation at the Simalungun University, where the author aims for a permanent career as a lecturer. Currently, in his passion for the fields of Civil Engineering and Technology Management, Sianturi frequently involves himself in various projects relating to the evaluation of machine performances to broaden his horizons.

I Made Dwipa Arta, Udayana University, Denpasar, Indonesia

I Made Dwipa Arta was born in Denpasar, Bali on 1983 and currently serves as Head of the Spatial Planning Section at the Gianyar Regency Public Works and Spatial Planning Office. He completed his Undergraduate education in the Department of Architecture (graduated in 2005), then continued his Masters education in the Department of Civil Engineering (graduated in 2018), followed with further professional education in the Professional Engineer Study Program in 2019 and is currently pursuing Doctoral education in the Doctoral Study Program of Engineering Science at Udayana University of Indonesia.

Yeti Rohayati, Universitas Langlangbuana, Bandung, Indonesia

Yeti Rohayati is a senior lecturer at Universitas Langlabuana and an invited lecturer in Sekolah Tinggi Ilmu Administrasi bandung. She is as an inisiator for constructing a digital gorvenance. She completed her Doctoral program at Digital Governance and has published several papers on Jurnal Sosial dan Humanis Sains, Insan Cendikia Mandiri, and other journals. In 2019, her research was supported by a grant by Kemenristekdikti and was completed in 2020, producing the outcome of models in contructing digital governance from the low up to high level. The model is hoped to be implemented for whole segment of Indonesia governance.

Diani Indah, Universitas Langlangbuana, Bandung, Indonesia

Diani Indah is a senior lecturer at Universitas Langlabuana whose expertise lies in organisation and management on government. She has completed her Doctoral degree, have published on several accredited journals, and received some grant research by the Indonesian Ministry of Research and Technology. Currently, Indah is preparing a research proposal involving collaboration of various parties in goverment management to produce a positive impact on Indonesia's governance.