The Analysis of Translation Techniques on Expository Text Translated by Machines Translation

Abstract

Translation technique is the way the translator changes source language to target language. In this dtusy, I employ Molina and Albir’s theory of translation techniques (2002) to analyze how translation technique occurs on expository text translated by machines translation. The purpose of this research is to describe phrases or words used by machines translation (Google Translate, PONS Translate, U-Dictionary and Papago Translate) connect to the translation techniques in translating expository text English-Indonesian. The writer used descriptive qualitative method. The data of this research is phrases or words in translated by machines translation in expository text. The source of the data is expository text which translated by Machine translation from English-Indonesian. The theory of Molina and Albir (2002) is applied in this research. The result of this research shown that the percentage of variation translation techniques from the first of machines translation is Google Translate found variation single is (56.25%), variation kuplet is (34.37%), variation triplet is (06.25%) and variation quarlet is (03.12%). The second of machines translation is PONS Translate found variation single is (67.74%), variation kuplet is (25.80%), variation triplet is (06.45%) and variation quarlet is (0%). The third of machines translation is U- Dictionary found variation single is (36.66%), variation kuplet is (46.66%), variation triplet is (13.33%) and variation quarlet is (03.33%). The fourth of machines translation is Papago Translate found variation single is (12.5%), variation kuplet is (33.37%), triplet variation (43.75%) and quarlet variation (09.37%). From the machines translation (Google Translate, PONS Translate, U- Dictionary, Papago Translate) in translating phrases or words found total variation is 125.

The result of the study shows that there are 11 techniques found in data. They are, namely adaptation, amplification, calque, compensation, description, language amplification, literal translation, modulation, particularization, reduction, transposition and variation. The total techniques of the data are 461. The percentage of each techniques are as follows: (1) adaptation occurs 1 time and represents 00.21%, (2) amplification occurs 7 times and represents 01.51%, (3) calque occurs 1 time and represents 00.21%, (4) compensation times 3 times and represents 00.65%, (5) description occurs 1 time and represents 00.21%, (6) linguistic amplification occurs 25 times and represents 05.42%, (7) literal translation occurs 376 times and represents 81.56%, (8) particularization occurs 1 time and represents 00.21%, (9) reduction occurs 25 times and represents 05.42, (10) transposition occurs 1 times and represents 00.21% and (11) variation occurs 20 times and represents 04.33%.From the finding above, it is described that machines translation better translated source text more phrases or words than the translation machines that the lower variation in translating phrases or words from expository text in English-Indonesian where Papago Translate. The hinger machines translation is Google Translate and PONS Translate that often made

phrases or words made translation techniques the good translation. Also the hinger translation techniques of analyzing text expository like to literal translation with 376 times and percentage 81.56%.