EEJ 9 (3) (2019) 382 - 390
English Education Journal
http://journal.unnes.ac.id/sju/index.php/eej
Accuracy, Readability and Acceptability in The Translation of
Android Xiaomi Redmi Note 4
Irfan Zahid Prasetya , Rudi Hartono, Issy Yuliasri
Universitas Negeri Semarang, Indonesia
Article Info
________________
Article History:
Recived 04 February
2019
Accepted 22 July 2019
Published 15
September 2019
________________
Keywords:
Implementation,
scaffolding technique,
senior high schools
____________________
Abstract
___________________________________________________________________
Android translation(s) were translated by multiple people/agencies during
multiple period of times, thus they are very prone to accuracy, readability and
acceptability errors. Based on that reason, I conducted this research to (1)
analyze and find out the accuracy of the translation in Xiaomi Redmi Note 4
smartphone, (2) readability of the translation of the smartphone, and (3) the
acceptability of the translation. The result of this study showed that all of the
accuracy, readability and acceptability of the original translation showed worse
results than the modified translation. For accuracy, Goff-Kfouri‘s and
Nababan‘s rubric both showed better result for the modified translation. For
readability by the translators, the average of original translation got 2.3
(negative) and modified got 3.8 (positive); whereas the end-users rated 2.4
(negative) and 3.8 (positive) respectively. For acceptability, the average of
original translation by the translators was rated 2.6 (negative) and the modified
translation got 3.7 (barely positive); and by the end users, the rates were 2.7
(negative) and 3.7 (positive).
© 2019 Universitas Negeri Semarang
Correspondence Address:
Jl. Kelud Utara 3 Kampus Pascasarjana UNNES, Semarang, Indonesia
E-mail: irfanzahidp@gmail.com
p-ISSN 2087-0108
e-ISSN 2502-4566
Irfan Zahid Prasetya, Rudi Hartono, Issy Yuliasri/ EEJ 9 (3) 2019 382- 390
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INTRODUCTION
Translators must not only understand the
two languages; i.e. source and target languages,
but also the other competences such as
communication competence, discourse, and
context of situation. Translators must be fully
capable of conveying correct messages from SL
to TL, so the people in TL environment can
understand the message fully (communicative
competence). They must be able to convey
messages that might seem invisible, only exist in
either TL or SL‘s culture, and other pragmatic
messages (discourse). They must also see the
whole context of situation of SL, so it will not
be misunderstood by the people in TL
environment. And last, translators must be able
to utilize correct linguistic elements in TL
environment, such as language style,
practicality, readability and literacy.
Commercial mobile phones, from earlier
apperance in Indonesia around year 2002, have
been translated to Indonesian language.
Although it is unclear which phone was
translated the first, Indonesian translation was
found in Nokia, Motorola, Siemens and Sony
Ericsson. The three brands were among the first
to be commercially available in Indonesian
language in a relatively affordable prices. Albeit
slight differences, there are similarities on the
translations among the brands. Among others,
―messages‖ is translated as ―pesan‖, ―call‖ is
―panggilan‖, and ―setting‖ is ―Setelan‖.
Android translations, however, are different in
each brand, even in each smartphone product.
Each brand employs individual or even several
translation agencies to translate their products.
Even then, one agency may not be employed
continuously by a brand. This causes potential
inconsistencies among phones in a brand, even
in one same phone. Not only that the
translations could be inconsistent, but the
quality could be compromised as well due to
different translation agency having different
quality control standards.
This research is focused on the accuracy,
readability and acceptability of the translation of
Xiaomi Redmi Note 4 smartphone. Accuracy,
taken from Molina & Albir (2002), is defined as
whether a translation possesses a certain degree
of correctness according to certain requirements.
For example, Nababan (2012) sets out three
degrees of accurateness: Accurate, Less
Accurate, and Not Accurate; each with
corresponding descriptions on the assessment
criteria. Skopos on the other hand does not
regard accurateness as important. Due to the
lack of equivalence, and the focus on whether
the reader understand or not makes accuracy
less meaningful than correctly placed sentence
structure. This, in essence, makes the
assessment of translation solely based on the
general understanding of target readers. Larson
(1984), however, added that accuracy means
that the information between the source and
target is simply correct. Any changes, addition
or deletions is conducted after comparing source
and target text, also thinking how good the
translation will be in the target situation. In
short, Larson‘s theory on accuracy is aligned
well with Skopos, although dynamic
equivalence still plays a huge part in the
translation process.
Translation
Catford (1965) referred translation as a
process of substituting a language into another
language. Larson (1984) explained further that a
translation is not only a change of language, but
also a transfer of the meaning, by the means of a
change in semantics, a constant transfer between
source and target language, and a clear re-
expression of a source text into the target
language. Larson claimed that only the while
the form changes, while other messages should
be encoded and re-expressed in target language
in a proper equivalence manner. Newmark
(1989) simplifies the term back by arguing that
translation is merely a process of converting any
utterance of any source language to the target
language. Larson (1984) further divides
translation into two, form-based and meaning-
based. Form-based translation, as the name
suggests, attempts to translate a text solely based
on the form of the source text. Meaning-based
Irfan Zahid Prasetya, Rudi Hartono, Issy Yuliasri/ EEJ 9 (3) 2019 382- 390
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translation is the contrary, where a translator
attempts to follow the source language.
Regarding translation strategy, Cohen
(1984), Loescher (1991) and Krings (1986)
argued that translation strategy is a translator‘s
conscious attempts and plans in solving
translation problems, as well as translator‘s
ability to distinguish the correct or incorrect
translating methods. Bell (1998), similar to the
above-mentioned theories, adds a differentiation
for the strategies: global and local. Global
strategy means that it deals with translation
strategy as a whole process—from start to finish,
and local means that it deals with certain
problems during certain smaller parts in the
translation. In relation to this research, skopos
deals with smaller translations, hence it used the
local strategy.
Accuracy, Readability, and Acceptability
Accuracy (Molina & Albir, 2002), is
defined as whether a translation possesses a
certain degree of correctness according to
certain requirements. Nababan (2012) sets out
three degrees of accurateness: Accurate, Less
Accurate, and Not Accurate; each with
corresponding descriptions on the assessment
criteria. Nida (1964) stated that translation is a
set of procedures in order to create a meaning in
a language target reader can understand. Larson
(1984), added that accuracy means that the
information between the source and target is
simply correct. Any changes, addition or
deletions is conducted after comparing source
and target text, also thinking how good the
translation will be in the target situation. In
short, Larson‘s theory on accuracy is aligned
well with Skopos theory.
Readability is a way of finding the best
translation methods and techniques to fit with
the source text so the readers can easily
understand them (Dubay, 2004). Hartono (2017)
further expands Larson‗s (1984) definition by
adding that readability can be determined by
diction, structure and organization of sentences,
spelling and even punctuations. Yolanda and
Yuliasri (2016) argues that readability prioritizes
the translation to sound natural instead of being
simply correct. Nababan (2012) also added that
in written translation, readability shows how
much a text is easily understood by the target
readers.
Acceptability is how a translated text
correctly reflects the target culture, norm and
linguistic rules (Nababan, 2012). In essence, the
translation must comply with the locally
acceptable rules; in terms of language style,
whether slang is involved or not, even multi-
meaning words in certain cultures. Acceptability
is required in order to create the best possible
translation that fits to the target reader. Similar
to readability, acceptability focuses less on
accuracy and focuses more on dynamic
equivalence.
Skopos Theory
Nord (1991) sees Skopos theory as an
intentional translation that must be judged to
see how well the text has fulfilled its role in the
target language situation. Baker (2001) further
explained that skopos is a new perspective in
translation study that reflects a more functional
and socio-cultural orientation in a translation,
where the source text exists merely to provide
the main information to produce the target text.
This is in line with Nord (1997), that deters the
function of the source text to emphasis on the
target translation, and that the translation result
may differ –slightly or drastically—from the
source text. Skopos is essentially a
communicative translation method but with
added function of goal- and action-oriented
purposes. In addition, skopos is necessary to
produce a highly practical application in the
target language.
Skopos is commonly found in the texts
that are related to culture. This include:
advertisements, novels and stories, movie
subtitles, songs, and poems. These texts can be
translated just as well using the translation
techniques and methods using Molina & Albir‘s
theories (2002), but skopos always puts heavy
emphasis on the target text; whereas Molina &
Albir‘s methods and techniques always put
more emphasis on the source text.
Irfan Zahid Prasetya, Rudi Hartono, Issy Yuliasri/ EEJ 9 (3) 2019 382- 390
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METHODS
To answer the research question, I used
descriptive qualitative research. The
questionnaire was taken by the users of Xiaomi
Redmi Note 4, both by the anonymous people
on the internet and in real life, and all with their
consents. It was conducted with a minimum a
total 25 takers combined: three professional
translators and 23 end-users. The questionnaire
rubrics were differentiated for the translators
and the end-users. For the translator, three four
rubrics were used: Goff-Kfouri‘s and Nababan‘s
rubric for translation accuracy, and Nababan‘s
rubric for translation redability and translation
acceptability. For the end-users, only two
rubrics were used: Nababan‘s rubric for
redability and acceptability.
For assessing accuracy, both Goff-
Kfouri‘s and Nababan‘s rubrics provide different
point of views for the assessments. Goff-Kfouri‘s
rubric provides in-depth analysis on each textual
elements of the translation, with focuses on
Fluency/Flow, Grammar, Terminology,
General Content, and Mechanics. The ratings
from Goff-Kfouri‘s rubric were not summarized,
rather they were assessed individually and for
each three translators. For the Nababan‘s rubric
on assessing accuracy, it gave general view on
the translation accuracy, as well as personal
comments on each of the questionnaire items.
There are several reasons why I use two
instruments that look radically different in terms
of analysis. The first is because Goff-Kfouri‘s
rubric does not regard translation technique as
important as the other factors such as grammar
and general context, which means translation
equivalence is not very important, and it is in-
line with the Skopos theme in my research. It
also offers more detailed marks on each
translation aspect. Nababan‘s rubric on the
other hand, deals more with equivalence
between source and target text. It also signifies a
more general approach in assessing the
accuracy. In conclusion, both specific and
general views are equally important in assessing
translation accuracy
For assessing translation readability and
acceptability, I used Nababan‘s instrument to
assess the readability directly from the
questionnaire takers. Readability analysis
usually takes quantitative forms, with up to ten
types of calculation. The calculation result from
all or part of them would then be compared with
average reading competence in certain regions
or countries. The problem with using such
calculation in translation is that, it does not
really show how good or how bad is a
translation from a subjective point of view—
especially by the actual readers—and the result
cannot be explained and further elaborated in
accordance to my purpose. Nordquist (2018)
shares his idea about readability formulas, that
they do not serve any purpose at all in actually
providing information regarding a translation
readability among the true target readers. He
also insists that readability is best being assessed
by the true target readers themselves. Certain
formulas such as Felsch‘ or SMOG‘s, require a
minimum of 100 word-count to be able to be
assessed, and texts found from cellphones are
mostly very short, thus will not produce any
result at all. This also applies to acceptability
analysis, where the instrument is similar to
readability‘s.
In assessing readability and acceptability,
the assessment was taken from the answers by
the end-user directly. If end-users gave their
rating of more than 62.5% of average (rated
3.4~5 for readability, and 1.0~3.4 for
acceptability) then it implied positive
understanding, thus the translation has good
readability. If the respondents show negative
understanding (rated 1.0~3.4 for readability,
and 3.4~5 for acceptability), then it would be
concluded that the original translation has
readability error. Negative Understanding is
where the questionnaire takers do not
understand the context of the original
translation provided in the questionnaire,
whereas Positive Understanding means that the
respondents understand the meaning implied.
The positive and negative understanding are
taken from each word or sentence by face-value.
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The original translations are provided
along with the modified translation of the same
context in random orders in each question. The
modified translations act as the distractor and a
comparison for the original translation. In
addition, if the average readability of text A is
higher than average readability of B, the
conclusion is that there is no readability error;
and if vice versa, there is a readability error.
RESULTS AND DISCUSSION
In this part, I presented the result of the
translation accuracy, readability and
acceptability, in this respective order, after
assessing the texts from Android Xiaomi Redmi
Note 4 smartphone.
Translation Accuracy
The assessment of translation accuracy is
only conducted for three professional translators
with two instruments each; one by Goff Kfouri
and the other by Nababan. The result of the
accuracy assessment is determined for each
number group (1a and 1b, 2a and 2b, etc). For
Goff-Kfouri‘s rubric, result were taken from the
average ratings of each number for each
criterion, without the ‗Mechanic‘ criterion.
From the results by the three translators, 4
criteria from Goff Kfouri‘s rubric showed 2.8 for
original translation and 3.6 for modified
translation; whereas the ‗mechanics‘ rating was
3.3 for original translation and 3.7 for modified
translation. The details can be seen below,
where ―#a‖ indicates original and ―#b‖
indicates modified translation.
Table 1. Average Result of Translation
Accuracy for Goff-Kfouri‘s Rubric
1a 1b 2a 2b 3a 3b
4 criteria 2.6 4.0 2.5 4.1 2.7 3.1
Mechanic 3.3 4.0 3.3 3.7 3.3 3.3
4a 4b 5a 5b
4 criteria 2.8 3.8 3.4 2.8
Mechanic 3.3 4.0 3.3 3.3
In assessing the translation accuracy
using Goff Kfouri‘s rubric, not only that the
question items were assessed at face value, but I
also added the backtranslations for comparing
the actual formal equivalence with the original
translation, and with the accuracy ratings the
translators gave. The analysis on this part of the
analysis was actually done one-item by one-
item, and there were no actual ‗overall analysis‘
except that from the average ratings, the
modified translation was found to have better
accuracy.
The individual analyses resulted in
several interesting findings. First of all, the
translators did not actually assess the pure
accuracy of the texts, but they actually regarded
the accuracy in relation with mostly readability.
The first instance of this occurred by the first
translator, on question item number ―3‖, where
the rating for ‗Terminology‘ criterion spiked
from 2 in ―3a‖ to 4 in ―3b‖—despite the original
translation was a faithful, formal translation.
There has yet any theory to mention this yet, so
I call this a ―paradox of accuracy‖.
Another interesting phenomenon I found
out was that, in certain instances, the translators
think that some commonly used terms in
Android translation, or technology-related
translation, were actually less accurate (or
probably less readable) than they actually worth.
This was first seen in question item ―5a‖,
regarding the translation of ―uninstall‖. The
weakness of Goff Kfouri‘s rubric is that it does
not provide an open-ended space for the
assessors. Comments are especially important
for accuracy, because I need the reason why the
translators put their ratings as such. The
instances above could not be explained with
mere numbers. This is where Nababan‘s rubric
comes in.
The second translation accuracy
assessment uses the instrument by Nababan
(2012 in Hartono, 2017). This instrument is
simpler but gives a space for open-ended
comments by the translators. The scale for
rating for Nababan‘s instrument are longer and
slightly more complicated, but envelops all
aspects at once; contrary to Goff-Kfouri that
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details each and every criterion with simpler
explanation for the ratings. The ratings in
Nababan‘s rubric are reversed than Goff
Kfouri‘s, hence 5 means the worst and 1 means
the best.
Table 2. Translation Accuracy Assessment by
Nababan‘s rubric
Translator Rating
Original
Translation
Modified
Translation
1 2.4 3.8
2 2 3.6
3 2.2 3.4
average 2.2 3.6
The analysis for this rubric was
individual. Each question item (or sometimes a
couple) was analyzed individually, while
sometimes comparing the results with their
respective Goff Kfouri‘s analysis and/or the
backtranslations. Just like the Goff-Kfouri‘s
analysis, there were also several interesting bits
to take notes on in this analysis. The first
instance among others was found in the first
translator‘s question item number ―5‖. In this
item analysis, the first translator claimed that he
has never heard of ―bongkar‖ to translate
―uninstall‖, and he put both ―5a & 5b‖ in not
very accurate rating. His comment on ―5b‖ was
that he agreed to translate ―install‖ to ―instal‖
but disagree to translate ―uninstall‖ to
―uninstal‖. It is okay to translate ―install ― to
‖instal‖ while ―uninstall‖ to
―bongkar/uninstal‖. If this looks inconsistent—
both are two terms of the exact same context,
but only antonyms—it is simply how it is
written in English language. English uses ―un-‖
prefix to show ―not-‖, but Indonesian language.
Another example for Goff Kfouri‘s
analysis was taken from the item number ―4‖.
For this number, all three translators gave better
rating for the modified translation than the
original, however in fact the original translation
is perfectly equivalent with the source text.
Despite that, all three translators think that the
accuracy of the modified translation –that was
less formally equivalent than the original
translation. The difference between them was
the grammatical element, where the original
translation applied the exact same grammatical
and structural rules as the English source. The
conclusion for this item was that the translators
might have thought of the readability along with
the accuracy; thus accuracy without readability
was deemed incomplete.
In the third example, taken from question
item number ―1‖, it was an example of how the
original intended meaning affects the
translation. Text in android are usually short
and does not have any cultural backgrounds
and/or appropriations. How the texts relate to
each other was from where the text was found
at, and the associated text related to them. In
inspecting ―1a‖ against the intended meaning
and the location of this text, this text was found
under the ―Security‖ menu, inside the general
―Settings‖. In this premise, the end-users
actually did not need the additional text. The
end-users already knew what the exact function
of this text and need no additional help, hence
the original translation served its purpose well.
However, there were some chances where a user
finds this text in other situations, e.g. from the
‗search‘ function, or from the ‗help‘ page within
the phone, or simply reading the one-off text
somewhere else. In the latter case, additional
information would help the reader understand
the immediate context without having to
research too much of the related background
information. In conclusion for question item
number 2, it still has a low accuracy rating.
Hence, the accuracy with slight relation to
readability of this text number ―1‖ was less
satisfactory that the modified translation scored
a better rating.
For ‗mechanics‘ part, all five question
items are analyzed as a whole. Mechanics is
how the translation is done, how much is
translated—be it contains omission or
addition—and simply whether it fits or not. It is
almost related to acceptability. The average
mark for the whole question items are 3.5;
detailed at 4 by the first translator assessor, 3 by
the second, and 3.5 by the third. The first and
second translators only filled homogenous
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numbers in all the question items; the first
translator assessor wrote 4, and the second
writes 3. These translators were assumedly did
not actually understand the meaning and
intention of Mechanics. For the third translator,
the average of ―5b‖ beats ―5a‖ by 1 rating, that
changed from 3 to 4. In conclusion on
Mechanics, is currently unmeasurable and
unable to be analyzed due to the other two
translators did not fully understand how to rate
them. In conclusion, this ‗Mechanics‘ analysis
would have deemed as better to be ignored.
From Nababan‘s rubric, the first
interesting instance was found from the first
translators‘ assessment on question item number
―3‖. The translator neither agreed or disagreed
with the shown terminology for ―bar‖,
translated to ―bar‖ in ―3a‖ and ―bilah‖ in ―3b‖,
and put the rating 3 for both. He gave an
alternative, that is ―panel‖. In this Nababan‘s
rubric, rating 3 means slight accuracy problem,
and he commented on the terminology only. In
relation to Goff-Kfouri‘s rubric, where the first
translator gave rating 2 in ―3a‖ to 4 in ―3b‖,
with the original translation was a actually
faithful, formal translation, it was proven by his
comment where both ―bar‖ (the borrowed
translation) and ―bilah‖ were thought to be not
good. The second translator on further
commented on item ―3‖ for a new translation
which is ―panel‖. Updated from the translator‘s
term preference, the translation becomes
―Notifikasi dan panel status‖.
The second instance was taken from the
first translator‘s question item number ―5‖. Here
the translator commented on ―5a‖, where he
claimed to never have heard of ―bongkar‖ (lit:
disassamble) being used to translate ―uninstall‖.
In ―5b‖ he said that ―uninstal‖ (with one ‗L‘)
was not a good choice to translate ―uninstall‖,
however he also said that he agreed on using
―instal‖ (one ‗L‘) to translate ―install‖. In the
respective Goff-Kfouri‘s analysis for this
question item, I concluded that ―bongkar‖ was
used in more practical fields, whereas ―uninstal‖
was simply the transliteration of the source.
Within the Skopos theory, although equivalence
did not matter, consistency was still important.
Consistency is when a term was used in
consistent way throughout the document
according to its correct context. In this example
―instal‖ was already correctly used within the
scope of applications, hence it was correct and
consistent.
Another interesting bit by Nababan‘s
instrument to assess translation accuracy was
seen at the question item number 1, where ―1a‖
got a 5 and ―1b‖ got a 1. This absolute drastic
change is accompanied with a comment that
implied alleged accusation for machine
translation, because ―for‖ was directly translated
to ―untuk‖. This comment by the second
translator was related to grammar and structure,
as ―for‖ was actually correctly translated.
However, it is deemed inaccurate and caused
another paradox of accuracy. Both
backtranslations of ―1a‖ have proven this—
where both were formally equivalent to the
source. Same as the structure, as was is also
proven to be exactly the same as the source text.
In conclusion for this item, this result further
strengthened the Skopos theory, that accuracy
does not always mean good translation, and that
the readers‘ perception is much more important.
In conclusion for translation accuracy by
both instuments, the accuracy of the original
translation is worse than the modified
translation. In Goff-Kfouri‘s non-averaged
rating results, the majority of the ratings showed
better ratings for the modified translation. This
was further proven by Nababan‘s rubric, where
the average ratings of the original translation by
the first, second, and third translator are 2.4, 2,
and 2.2 respectively; whereas for the modified
translation, the ratings are 3.8, 3.6, and 3.4
respectively, which indicate better accuracy.
Translation Readability
The translation readability was assessed
by the three translators and the end-users. In
readability analysis, the lower the number is, the
worse the translation readability is, with the
range of 1 to 5. From the three translators, the
total average is 2.3, tallied at 2.3 by the first
translator, 2.3 by the second translator, and 2.2
by the third translator. Meanwhile, the total
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average for the modified translation falls at 3.8,
with 3.8 by the first translator, 4 by the second
translator, and 3.6 by the third translator. Thus
the original translation had negative
understanding, while the modified translation
had positive understanding. For the result by the
23 end-users, the average rating for the original
translation by the end-users is 2.4, and it
indicates a negative understanding. The average
rating for the modified translation is 3.8, which
indicates a positive understanding. Thus it is
concluded that the modified translation has
better readability than the original translation.
Translation Acceptability
The translation acceptability assessment
took the same approach as the readability
counterpart. In acceptability analysis, the lower
the number, the better the translation
acceptability is. For the translation acceptability
assessment by the three translators is that the
acceptability of the original translation is lower
than the modified translation. The rating for
original translation is 2.5, and the modified
translation, the rating is 3.6. In this analysis, the
original translation is unacceptable whereas the
modified translation is adequately acceptable.
Meanwhile, the translation acceptability result
by the end-users showed that the original
translation is very unacceptable with 2.2 rating,
whereas the modified translation is fairly
acceptable with 3.7 rating. In conclusion, the
modified translation has better acceptability
than the original translation.
CONCLUSION
In conclusion by all the analysis, the
quality of the translation that is accuracy,
readability and acceptability of Xiaomi Redmi
Note 4 is less than satisfactory, as proven that
the modified translation always gets higher
overall rating than the original translations.
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