THE ANALYSIS OF TRANSLATION TECHNIQUES AND QUALITY OF TRANSLATION OF THE WEBSITE “FRIENDSTER.COM”

THESIS

Submitted as a Partial Fulfilment of the Requirements for Sarjana Sastra Degree at English Department

By: LAMBANG PRAKOSO C 0305040

ENGLISH DEPARTMENT FACULTY OF LETTERS AND FINE ARTS SEBELAS MARET UNIVERSITY SURAKARTA 2010

THESIS APPROVAL THE ANALYSIS OF TRANSLATION TECHNIQUES AND QUALITY OF TRANSLATION OF THE WEBSITE “FRIENDSTER.COM”

Written By: Lambang Prakoso C 0305040

Approved to be examined before the Board of Examiners Faculty of Letters and Fine Arts Sebelas Maret University

Thesis Consultant:

Ida Kusumadewi, SS, MA NIP. 19710525 199802 2 001

Head of English Department

Dr. Djatmika, MA NIP. 19670726 199302 1 001

ii THE ANALYSIS OF TRANSLATION TERCHNIQUES AND QUALITY OF TRANSLATION OF THE WEBSITE “FRIENDSTER.COM”

Written By: Lambang Prakoso C 0305040

Accepted and Approved by the Board of Examiners Faculty of Letters and Fine Arts Sebelas Maret University On

Position Name Signature

Chairman Dr. Djatmika, MA (…………………) NIP. 19670726 199302 1 001

Secretary Drs. Agus Hari Wibowo, MA (………………....) NIP. 19670830 199302 1 001

First Examiner Ida Kusuma Dewi, SS, MA (…………………) NIP. 19710525 199802 2 001

Second Examiner Dr. Tri Wiratno, MA (………………. ..) NIP. 19610914 198703 1 001

The Dean of Faculty of Letters and Fine Arts Sebelas Maret University

Drs. Sudarno, MA NIP. 19530314 198506 1 001

iii

PRONOUNCEMENT

Name : Lambang Prakoso

NIM : C 0305040

Stated wholeheartedly that the thesis entitled “The Analysis of

Translation Techniques and Quality of Translation of the Website

Friendster.com” is originally made by the researcher. It is not plagiarism, nor made by the others. The things related to other people’s work are written in quotation and included within the bibliography.

If it is then proved that the researcher cheats, the researcher is ready to take the responsibility.

Surakarta, Februari 2010

The researcher,

Lambang Prakoso

iv

MOTTO

v “Surely with difficulty is ease. With difficulty is

surely eased.” (QS: Alam Nasyrah : 5-6)

v You can if you think you can. (George Reeves)

v Imagination is more important than knowledge.

(Albert Einstein)

v

DEDICATION

This thesis is dedicated to:

Allah SWT, the Lord of the Universe

The Prophet Mohammed, Peace be Upon Him

My beloved Ibu and Bapak

My Little Brother

vi

ACKNOWLEDGMENT

Bismillahirrohmannirrohim Alhamdulillah, I want to thank, Allah SWT, for everything given to me. With all blessing, love, and guidance given to me, I can finish this thesis as a partial fulfilment of graduating requirement of the Sarjana Degree. In finishing this thesis, I got supports and helps from people around me. Therefore, I want to give my deepest gratitude to all the people who have given important contributions. It goes to: 1. The Dean of the Faculty of Letters and Fine Arts, for approving this thesis. 2. The Head of the English Department, Dr. Djatmika, MA, for his permission to conduct this thesis. 3. My thesis advisor, Ida Kusuma Dewi, SS, MA, for her advices and assistance. Thank you very much. 4. Drs. Hari Wibowo, MA and Dr. Tri Wiratno, for being my thesis examiners. 5. My academic consultant, Taufik Al Makmun, SS, for his assistance during my study. 6. All the lecturers who have taught and gave me precious knowledge. Thank you very much for many unforgettable classes we had. 7. The three raters, Mr. Heri Nababan, Mr. Sumardiono, and Mr. Alif for the valuable contributions in this thesis. 8. The 18 respondents from XII TKJ SMK Negeri 1 Boyolali for being my respondents. 9. My beloved Ibu (Tutut Daryani) and Bapak (Sukadi) for the big love and cares. Thank you for your supports and prays. You are wonderful parents ever. My little brother, Ruruh Kayadi.

vii 10. Pakdhe Noto. Thank you for your helps and your suggestions. You are like my second father. Thank you for your inspiring words: “dadi wong ki sing sabar, kabeh kuwi anggepen prihatin.”, “ora usah meri, rejekine uwong ki bedo-bedo, bejone uwong ki bedo-bedo.”, and also “pikiran orang bisa berubah tak hanya dalam hitungan bulan, minggu, hari, ataupun jam, hanya dalam 1 detik pun pikiran orang bisa berubah.” I will always remember that. 11. My beloved friends in ED 2005. “Semangat”, who I can not mention one by one. Thanks for our togetherness guys. It is so nice to have friends like you all. 12. Mas Edy Triyanto, Mas Edy M Fata, and Mas Najib. Thank you for being the best brothers. Thanks for your helps. I really appreciate your advices and your suggestions in making my thesis. 13. My friends in futsal team, Andika, Adwin, Febri, Alwi, si Bo, Tori, Rudy, Ucup, Danang, etc. Thanks for all of your jokes guys. 14. Mbak Cindy and Mbak Hilda. I think we should make a ‘Trio’. 15. The Pokeran’s Tim, Himawan ‘Pakdhe’, Giwang, Daniel, Jusmar, Makna, Mbak Pipit, Kang Ipul, etc. Thanks for the happiness guys.

I realize that this thesis is far from being perfect. Any supporting criticisms and suggestions are welcomed.

Lambang Prakoso

viii

TABLE OF CONTENTS

Approval by Thesis Consultant ii

Approval by Board of Examiners iii

Pronouncement iv

Motto v

Dedication vi

Acknowledgment vii

Table of Contents ix

List of Tables xii

Abstract xiii

CHAPTER I : INTRODUCTION

A. Research Background 1

B. Research Limitation 5

C. Problem Statement 5

D. Research Benefits 5

E. Thesis Organization 6

CHAPTER II : LITERATURE REVIEW

A. Definition of Translation 7

B. Types of Translation 8

C. Equivalence 13

ix D. Translation Techniques 15

E. Translation Quality Assessment 22

F. Friendster 25

G. Website Localization 26

CHAPTER III: RESEARCH METHODOLOGY

A. Type of Research 29

B. Data Source 29

C. Sample and Sampling Technique 30

D. Method of Data Collection 31

E. Technique Data Analysis 33

F. Research Procedure 34

CHAPTER IV: ANALYSIS

A. Introduction 35

B. Analysis

1. Translation Techniques 35

2. Accuracy 47

3. Acceptability 53

4. Readability 59

C. Discussion 66

x CHAPTER V : CONCLUSION AND RECOMMENDATION

A. Conclusion 76

B. Recommendation 77

BIBLIOGRAPHY

APPENDICES

xi

LIST OF TABLES

Table 4.1.1 : Addition Technique 37 Table 4.1.2 : Borrowing or Borrowing plus Explanation 38 Table 4.1.3 : Naturalization 39 Table 4.1.4 : Literal Translation 40 Table 4.1.5 : Free Translation 41 Table 4.1.6 : Translation Shifts 45 Table 4.1.7 : Translation Techniques 46 Table 4.2.1 : Accuracy 49 Table 4.2.2 : Acceptability 55 Table 4.2.3 : Readability 60 Table 4.2.4 : Translation techniques and TQA 67

xii ABSTRACT

Lambang Prakoso. C0305040. The Analysis of Translation Techniques and Quality of Translation of the Website Friendster.com. Undergraduate Thesis: Surakarta. English Departments, Faculty of Letters and Fine Arts. Sebelas Maret University. 2010.

This research belongs to a mixed research of qualitative and quantitative methodology employing descriptive method. It is aimed to describe the translation techniques occurred in the translation and the quality assessment of the translation from the website friendster.com. It is also aimed to find out the quality assessment that covers accuracy, acceptability and readability of the phrases of website friendster.com. This research applies purposive sampling as the sampling technique, since the samples are chosen and determined by the researcher. This research is conducted based on primary and secondary data. The primary data consists of 172 phrases taken from the friendster.com and its translation. The secondary data are taken by distributing questionnaires to some raters and respondents. The analysis shows that the translation techniques used by the translator in translating the friendster.com are translation shifts, literal translation, naturalization, borrowing or borrowing plus explanation, addition, and free translation. The analysis on translation accuracy shows that there are 146 data considered to be accurate translation. There 26 data considered to be less accurate with classification It means that, in general, the translation is accurate. The analysis on translation acceptability shows that there are 157 data considered to be acceptable translation. There are 15 data considered to be less acceptable. The analysis on translation readability shows that there are 5 data considered to be readable translation with classification A. There are 101 data considered to be less readable with classification B. There are 66 data considered to be unreadable translation with classification C. It means that, in general, the translation is less readable. It is hoped that this thesis will be beneficial for the English Department students, especially who study translation, as one of the additional source to enlarge and sharpen knowledge about translation, especially related with website translation. Moreover, they can use this research as a reference to conduct a further research related to this study. The researcher also hopes that this thesis can also stimulate other researchers to conduct a further study related to website translation. This research is also recommended to the translator and designer of friendster.com to improve the quality of the website.

xiii CHAPTER I

INTRODUCTION

A. Research Background

The use of English as the international language is increasing, in line with the development of science, technology and literature. This phenomenon is proven by the large numbers of websites that are growing rapidly recently. In the globalization era, many people use websites as their part of life. There are many websites made for different purposes and used by many people in different countries, and most of websites are written in English. The fact that not all people in the world speak and understand English as their daily language might raise problems concerning the way in using websites. In this case, the role of translation is strongly needed in mediating the publishers of the websites and the users who do not master English well.

There is a fact that translating websites is different from translating books.

In translating a book, the translator has an opportunity to give some additional information of the translation because there is no limitation of space, except if there is limitation from the publisher of the book. In translating websites, on the contrary, the translator can not be free to give any additional information of the translation as he or she wants because of the limited space. The structure of the translation website should be the same as the structure of the original web which has a fixed template.

xiv Each website uses different template which has been modified by the creator. In some parts of websites the texts are written in the box. The translators can not put any additional information if the texts are written on the box because of the limited space caused by the box shape. That makes translator unable to accommodate more texts on it. Meanwhile, for the texts that are written outside of the box, the translator can put any additional information, even though it can not be done as freely as translating books due to the limited space of the template of the website.

Friendster is an online social network website. It has the form like usual websites that has template containing texts that are written inside and outside of boxes. Friendster has a language link that can change the displayed text into

Indonesian for the users in Indonesia. It means that there should be translations from English into Indonesian. However, in the first look of the translation, the researcher found that some of the translations sound unnatural as Indonesian expressions. For example, the phrase “dating men” is translated into “pria berkencan”, and “relationship with men” is translated into “hubungan dengan pria”. Those translations are accurate. The level of acceptability of the translations, however, is low.

The following are examples taken from friendster which show the limitation of space caused by the box shape:

View Messages Create Blog Edit Friends Edit Comments Customize Page Edit Profile Edit Photos

xv The above source text is translated as follows:

Lihat Pesan Buat Blog Edit Teman Edit Komentar Ubah Halaman Edit Profil Edit Foto

The following example shows another text of friendster that is not written in a box:

Source text : Current courses Translated into: Kelas yang diikuti saat ini.

The above example shows that, the source text is “current courses”, and then the translator translates it into “Kelas yang diikuti saat ini”. This shows that the translator has to put additional information to give more understanding information according to the source text, because the text is not written in the box.

The translator adds “yang diikuti” which makes the translation easier to understand rather than if it is translated into “kelas saat ini”.

It shows that in translating website, a translator needs to consider not only the accuracy, the readability, and the acceptability of the translations, but also the limited space of the website.

The above discussion shows that website translation is something interesting to investigate. It leads the researcher to analyze the Indonesian translation of friendster.com.

Friendster is an online social networking service. It is the first online social network and was founded in California by Jonathan Abrams in the year of

xvi 2002. It is growing very rapidly in recent times and widely used in Asia.

Friendster has over 50 million users worldwide. Friendster is available in many different languages. It was originally published in English, and then the publisher created a language link that can change the text displayed on the site to Chinese,

Japanese, Korean, Thailand, Indonesian, or Spanish for other users that do not understand English well. (www.webupon.com/Social-Networks/The-History-of-

Friendster.102 940)

Friendster had been introduced in Indonesia in 2004 and started to be popular since the website could be accessed in mobile mode since 2006. Even thought there are other new popular online social networks websites in Indonesia, friendster still becomes a part of Indonesian lifestyle. According to small project that the researcher had done in some internet booths, 3 of 5 people that use internet are still accessing friendster, even though they had another account for some other online social networks.

Unlike other online social network websites, friendster is relatively easy to be operated because it uses simple template of website that eases the users in accessing it. The users also can change the profile background picture or colour and choose some interesting background by searching from the special website that the friendster had prepared by forum of friendster. The users can modify the profile background picture based on the picture that they want by uploading the picture to certain websites that have relation with the background maker of friendster.

xvii B. Research Limitation

The research limitation is needed to keep our research always focus to the problem statement. The focus of the analysis is only on the phrases (the unit of translation analyzed) of the website friendster.com. This research is focused on analyzing the translation techniques that are used by the translator in translating the phrases of friendster.com and the quality of the translations in terms of accuracy, acceptability, and readability.

C. Problem Statements

In this research, the researcher proposes the following problems:

1. What translation techniques are used by the translator in translating phrases of

the website friendster.com?

2. How do the techniques influence the quality of translation in terms of

accuracy, acceptability, and readability of the web friendster.com?

D. Research Benefits

The researcher expects that this research will be useful for:

1. The publisher,

The publisher of friendster.com can make improvement in their translation.

2. English department student,

The research expects that this research can be an additional input in the study

of translation.

xviii 3. Other researchers,

The research expects that this research can be an additional input as a reference in conducting similar researches.

E. Thesis Organization

The present thesis is organized as follows:

Chapter I: Introduction, containing: research background, research limitation problem statements, research objectives, research benefits, and thesis organization.

Chapter II: Literature Review, containing: definition of translation, types of translation, accuracy, acceptability, readability in translation, translation strategy, and about friendster.

Chapter III: Research Methodology, consisting: type of research, data source, sample and sampling technique, method of data collection, technique data analysis, and research procedure.

Chapter IV: Data Analysis, consisting: introduction, translation techniques analysis, accuracy analysis, acceptability analysis, and readability analysis, discussion.

Chapter V: Conclusions and Recommendations.

xix CHAPTER II

LITERATURE REVIEW

A. Definition of Translation

Experts propose different definitions of translation. The most famous are

Nida and Taber, Larson, Peter Newmark and Roger T. Bell. Nida and Taber in their book entitled The Theory and Practice of Translation, the definition of translation as follows “Translating consist of reproducing the receptor language the closest natural equivalence of the source language, first in terms of meaning and secondly in terms of style” (1974:14).

Peter Newmark defines translation as “a craft consisting in the attempt to replace a written message and/or statement in one language by the same message and/or statement in another language.” (1988:7). In this definition, Newmark focuses only on the replacement of written message, and/or statement without considering the style used in the text.

Bell states “translation is the expression in another language (or target language) of what has been expressed in another, source language, preserving semantic and stylistic equivalences” (1991:5). Larson defines that, “Translation consists of transferring the meaning of the source language in the receptor language.” (1984:3). Based on the explanation above, the TL should have the same meaning as what is brought in the SL.

xx B. Types of Translation

According to Nababan (2003), there are ten types of translation. The use of different types of translation is caused by several factors, which are (1) the differences of the source and target language systems, (2) the differences of the fields of the translated texts, (3) consideration that translation is a means of communication and (4) the differences of the purposes of the translation.

1. Word for word translation

Using this type of translation, translator only replaces source language words with their equivalences in target language. The arrangement of the words in source text is the same as that in the target text.

Example: I bought a book yesterday.

Saya membeli sebuah buku kemarin.

The example above shows that the sentence is translated word by word.

It can happen because the sentence structure between source text and target text are the same.

2. Free translation

Catford states “A free translation is always abounded-equivalences shunt up and down the rank scale, tend to be at the higher ranks sometimes between larger units than the sentences” (1965:25). In free translation, equivalences are not achieved at word or sentence level but at a paragraph or a discourse level.

Translator has to be able to understand the whole message of a paragraph or a

xxi discourse thoroughly and then express the message in target language. Free translation is usually used to translate idiomatic expressions and proverbs.

Example: killing two birds with one stone

Sekali merengkuh dayung, dua tiga pulau terlampaui

The example above shows that in free translation the priority is the equivalence of the meaning rather the form. The translator freely expresses the translated sentences in target language as long as the message is currently transferred.

3. Literal translation

Literal translation is similar to word for word translation but they are different in the way that in this type of translation, translator does not simply replace words in source language with their equivalences but he or she also adjusts the arrangement of the words to word arrangement rule in the target language.

Example: good time

waktu yang tepat

In this translation, the adjective “good” which comes before the noun

“time” is re-arranged and placed after the noun in target language. It is because in

Indonesian language, the rule for this kind of construction is that the adjective comes after the noun.

xxii 4. Dynamic translation

In this type of translation, message from source language is expressed in natural expressions in target language.

Example: the writer has organized his book for one year

penulis telah menyusun bukunya selama satu tahun

In this translation, the translator prefers to translate “organized” into

“menyusun” rather than into “mengorganisasi”. It makes the translation sound natural.

5. Pragmatic translation

This type of translation emphasizes on the accuracy of the message in target language which is appropriate with the use in the source language.

Pragmatic translation does not focus on the aesthetic aspect of the sentences in the source language.

Example: for baby: after bathing, dust generously over the skin, taking

special care where the skin folds and creases. Use after baby’s

bath and every change

(untuk bayi: taburkan bedak pada seluruh kulit sehabis mandi,

terutama pada bagian-bagian lipatan kulit. Gunakan pada

setiap menggantikan popok dan sehabis mandi).

(Nababan, 2003:35)

xxiii 6. Aesthetic-poetic translation

This type of translation is different from pragmatic translation. If pragmatic translation emphasizes only on the accuracy of the message, aesthetic- poetic translation emphasizes on the accuracy of the message as well as the impression, emotion and feeling aroused by the text and the beauty of the language.

Example: Di luar salju terus. Hampir pagi.

Tubuhmu terbit dari berahi.

Angin menembus. Hilang lagi.

Nafasmu membayang dalam dingin. Mencari.

Outside snow falls. Almost morning.

Your body shaped in sensual feeling.

The wind pierces. And is clearing.

Your breath a shadow in the cold. Searching.

(Machali, 2000:80)

The translation of the poetry attempts to preserve the beauty of the text by producing regular rhymed –i in the target text. Also, the translator emphasizes his/her intention in the accuracy and the diction of translation due to the feeling, emotion, and impression from the source text.

xxiv 7. Linguistic translation

Linguistic translation refers to translation attempting to make implicit linguistic information in source language become explicit. This type of translation uses back-transformation and meaning component analysis to fulfill its objective.

Translator finds linguistic information, such as morphemes, words, phrases, clauses and sentences and makes the information explicit.

Example: They are sailing boats. (a)

They are now sailing boats. (b)

They are the sailing boats. (c)

Sentence (a) is ambiguous since it may mean a declarative sentence stating that “they”, referring to persons, are sailing boats on water at present and it may also mean a declarative sentence indicating several sailing boats. Sentences (b) and (c) make the information explicit.

8. Communicative translation

Like the other types of translation, communicative translation emphasizes on the transfer of message. Newmark in Nababan (2003) regards translation as social phenomenon having multi-dimension. Source and target languages, culture, source text writer, translator and readers need to be considered. Communicative translation also concerns about the effectiveness of the translation and the effect it arises (p. 29).

xxv Example: Open the door, please.

Open the door!

Both sentences have different effects and will result different response.

Therefore, they must be translated into different expressions. They should be translated into “Tolong tutup pintunya.” and “Tutup pintunya!”.

C. Equivalence

A translation activity cannot be separated from finding out the source language equivalences in the target language. Equivalence, as pointed out by Barnstone in Nababan (2003:99), is the core of translation. It means that transferring message of a text is always dealt with equivalence.

1. Equivalence at word level

The first attention of the translator, in translation process, is related to the meaning of word in the source language text. Word, defined by Bolinger and Sears in Mona Baker (1992:11), is the smallest unit of language that can be used by it. This is possible because every word conveys a certain meaning. As the smallest unit of language conveying the meaning, words become a starting point for the translator to understand the whole message of the text. Equivalence at word level is related to the lexical meaning of a word. This lexical meaning can be thought as the specific value the word has in a particular linguistic system. It means that every word has specific meaning that differentiates it from the other words. 2. Equivalence above word level

When co-occur with other words, words can reproduce a particular meaning in form of phrase, expression or idiom and these are called collocation. Collocation explained by Mona Baker (1992:47) as the tendency of certain words to co-occur regularly in a given language, has a pattern or form, which is arbitrary in building a certain meaning. However, when two words collocate, the relationship can hold among all or several of their various forms, combined in any grammatically acceptable order. Dry, for instance, can be easily explained what it means and it is potential to collocate with such words as voice, humour becoming new words with new meaning such as dry voice, dry humour. The collocational meaning of dry voice is different from the prepositional meaning of dry and voice. Dry voice means ‘cold speaking in the sense of not expressing emotion. The translator will be considered fail to catch the meaning of dry voice if he/she translates this as ‘a voice which is not moist’. Generally speaking, collocations are fairly flexible patterns of language, which allow several variations in form. In it’s extend, collocation produces idiom such as good morning, merry Christmas.

3. Grammatical equivalence

Grammar, explained by Mona Baker (1992:83), is organized among two main dimensions; morphology and syntax. The first one covers the structure of words, the way in which the form of a word changes to indicate specific contrast in the grammatical system. The last covers the grammatical structure of groups, clauses, and sentences. The syntactic structure of a language determines certain restrictions on the way messages may be organized in that language. Grammatical equivalence is dealing with how the translator transfers the grammatical meaning of the source language to the target language. This is how he/she interprets, for instance, the use of tense, number or gender into another language.

D. Translation Techniques

As translator, in translating process the translator should apply techniques to produce a good translation, the perception of translation as the final product of

xxvi the translated text in relation to the source text. Translation technique is a specific textual procedure for translating a particular structure or linguistic item.

Translation technique is the special techniques used by translators when transferring the message of the source language into the target language, includes the choice of equivalents. Translation technique is a procedure to analyze and classify how the translation equivalence happens and to be applied on different linguistic unit. (http://www.emanueltov.info/docs/papers/16.trans.techn.1999.pdf)

1. Addition.

Addition can be divided into two types: the first is addition for

structural reason and the second is addition for semantic reason. Addition

for structural reason means that the translator adds certain word in the

target text due to the difference structure of the source and target language.

The second type is addition for semantic reason. This technique is

applied for the sake of meaning clarity. The translator, in this case, adds

some additional information to the text because of the consideration that

the reader would need that information and without it they would have

difficulties in understanding the text. The additional information can be

put within the text, at the bottom of the text as notes, at the end of the

chapter or at the end of the book (Newmark, 1988).

Example:

Source Text: The skin, which is hard and scaly, is grayish in color, thus helping to camouflage it from predators when underwater.

xxvii Target Text: Kulitnya, yang keras dan bersisik, berwarna abu-abu. Dengan demikian, kulit ini membantunya berkamuflase, menyesuaikan diri dengan keadaan lingkungan untuk menyelamatkan diri dari predator, hewan pemangsa, jika berada di dalam air. (Taken from Suryawinata, 2000: 75). In above example, the translator gives additional information to the

biological term in the text. Translator adds the phrase menyesuaikan diri

dengan keadaan lingkungan to the word camouflage and hewan pemangsa

to explain the word predator.

2. Borrowing or borrowing plus explanation.

This technique is particularly common in dealing with culture-specific items and modern concepts. The loan word with explanation is very useful when the word in question is repeated several times in the text. Once explained, the loan word can then be used on its own; the readers can understand it and is not distracted by further lengthy explanation. Mona Baker (1992). Example: SL: Transferring and exchanging information Bluetooth wireless technology TL: Memindahkan dan saling menukar informasi teknologi tanpa kabel Bluetooth Bluetooth is a new technology and it does not have the equivalence in Indonesian language. The way to solve the problem is by borrowing the word without translating it.

3. Naturalization.

This technique succeeds transference and adapts the SL word first to the normal pronunciation, then to the normal morphology (word-forms) of the TL (Newmark, 1988). Example: SL: Taxi TL: Taksi SL: Mall TL: Mal

4. Literal Translation.

Literal translation is a translation that follows closely the form of the

source text, known as word-for-word translation (Larson: 1984). It focuses

on the form and structure of the source text.

Example:

xxviii

SL : I bought a book yesterday.

TL :Saya membeli sebuah buku kemarin.

5. Deletion (omission).

This technique may sound rather drastic, but in fact it does no harm to omit translating a word or expression in some contexts. If the meaning conveyed by a particular item or expression is not vital enough to the development of the text to justify distracting the reader with lengthy explanations, translators can and often do simply omit translating the word or expression in question. Example: SL : Mobile phone can be used, for example, to send

message and to make call.

TL : Telepon genggam dapat digunakan untuk mengirim

pesan dan menelepon.

The above example shows that the word “for example” is omitted. It

does not distort the message since the word omitted does not give a

significant meaning.

6. Free Translation.

Free translation is translation technique that places meaning as the highest priority. It means that the translator task is to deliver meaning exactly the same as the original although with totally different structure and wording. Example: SL : His heart is in the right place.

TL : Dia baik hati. (Nababan, 2003: 33).

7. Translation Shifts. This technique is used in order to overcome the problem related to

different language systems. The actual term shift was introduced by

Catford (1965), who distinguishes formal correspondence, which exists

between source and target categories that occupy approximately the same

xxix place in their respective systems, and translational equivalence, which

holds between two portions of texts that are actually translations of each

other. A shift has occurred if there are “departures from formal

correspondence” (p.73) between source and target texts, i.e. if translational

equivalents are not formal correspondents.

According to Catford, there are two major types of shifts: level shifts and category shifts. Level shifts are shifts between grammar and lexis, e.g. the translation of verbal aspect by means of an adverb or vice versa. Category shifts are further subdivided into structure shifts (e.g. a change in clause structure), class shifts (e.g. a change in word class), unit shifts (e.g. translating a phrase with a clause), and intra-system shifts (e.g. a change in number even though the languages have the same number system). (Cyrus: 2006)

a. StructureShifts.

This type involves a grammatical change between the structure of the ST and TT. Catford (1965) states that this shift, can occur at all rank of grammar; at group rank and at clause ranks. Example: SL: green shirt TL: kaos hijau The example of SL is a noun phrase and the structure is M (green) and H (shirt), whereas the TL noun phrase structure is H (kaos) and M (hijau). The example above shows the structural shift is found at the group rank. The structure of English noun phrase will automatically change as it shown in the example above, if it is translated into Indonesian. Example: SL: He took that stone S F/P C TL: Batu itu diambil-nya C P S From the example above, the syntactic function of the SL clause is: ‘he’ as Subject, ‘took’ as finite/predicator, ‘that stone’ as complement. Meanwhile, in TL there are some changes. The TL clause syntactic function is: “batu ini” as subject, “diambil” as predicator, “-nya” as complement. In SL, the position of the word ‘he’ is as subject. The word ‘he’ is replaced by the word “-nya” in TL and it has position as complement. In SL, the phrase ‘that stone’ functions as complement. Meanwhile, the phrase itself changes into the phrase “batu ini” in TL and its position as subject. The syntactic function of the SL clause is S - F/P - C, whereas the syntactic function of the TL clause is C - P - S. The example shows a structural shift at clause rank.

b. Class shifts or Category shift).

Translation shift is called class shift when a SL item is translated with a TL item which belongs to different grammatical class. As stated by Catford (1965) class shift occurs when the translation equivalent of a SL item is a member of a different class from the original item. Example: SL: He’s in danger TL: Dia dalam keadaan bahaya (Taken from Simatupang, 2000:91)

xxx The word “danger” in the SL has syntactic category as Noun, and translated/changes into “bahaya” in the TL. The word “bahaya” in syntactic category is an adjective. The example shows a class shift from noun into adjective.

c. Unit shifts (is similar to level shift; is similar to rank shifts).

This type of translation shift involves change in rank. As stated by Catford (1965:79) that unit shift occurs when the translation equivalent of a unit at one rank in the SL is a member of a different rank in the TL. Example: SL: He walks slowly TL: Dia berjalan dengan lamban From the example, it can be seen that the adverb “slowly” in the SL is replaced by the prepositional phrase “dengan pelan” in the TL. There is unit shift from word “slowly” into “dengan pelan”.

E. Translation Quality Assessment

Nababan (2003: 83) states that “assessing the quality of a translation means criticizing a literature work.” As there is neither a definitive reading of a text or a perfect rendering which achieves the goals of ST, translation quality assessment and criticism could go forever. The aim of criticizing a literature work is to find out the strengths and the weaknesses of a translation.

(http://www.erudit.org/revue/meta/2000/v45/n3/001878ar.pdf)

Larson (1998) mentions that a translation must be examined since a translator needs to make sure the accuracy, the clarity and the nature of a translation. This is similar to the procedure employed by Nababan (2004) in his research on translation process, practices, and products of professional Indonesian translator. Indirectly, a good translation shows that the translator has a good capability to translate and vice versa. (Nababan, 2003) The quality assessment covers three points; readability, acceptability and accuracy. Nababan (2004) adds

xxxi that acceptability as the third factor that is considered important in assessing translation quality.

1. Accuracy

Shuttleworth and Cowie (1997) define accuracy as a term used in translation evaluation to refer to the extent to which a translation matches its original. The accuracy of the message is an important thing in translation. Accuracy is a factor determining the quality of translation. Accuracy also means that the message of the source text is transferred into target text correctly and the translation can be understood by the target readers easily. A translation is considered to be accurate if it conveys the meaning of the source language to the target language correctly. The target readers of the translation should have the same interpretation, information, understanding, and feeling as the writers or the readers from the source of the texts. From the statement, it can be seen that preservation of meaning is a very important aspect in translation. The sameness in meaning is one of the factors determining the quality of a translation. Therefore, a translator has to be able to preserve the meaning or message of the original text.

In conclusion, to be able to produce accurate translations, a translator has to preserve the meaning contained in the source text, attempt to create equivalent response and purpose through the translation he or she produces as well as produce translations which have similar style and manner of writing as the source texts.

2. Acceptability

Acceptability of a text refers to the natural “feel” of the translation. A translation which leans toward acceptability can thus be thought as fulfilling the requirement of “reading as an original” that is written in target language rather than that of “reading as the original”. (Shuttleworth and Cowie, 1997)

A translation must be acceptable for its readers. A translator should be able to produce translation which is natural according to target language system. A

xxxii good translation is a translation which does not replicate the characteristics of source language (Sadtono, 1985). A translator should express the message he or she translates appropriate with the literary norms of target language.

(Suryawinata: 2000).

3. Readability

“Readability refers to how naturally and easily a translation can be read.”

(www.geocities.com). Readability is important in translation because translation cannot be separated from reading activity (Nababan: 2003). Therefore, a translator has to pay attention to this aspect. It is because readability influences the readers’ understanding of the message of a translation. A translation will be easier to understand if it is easy to read.

There are many factors influencing the readability of a text. Basically, there are four main factors. The first factor is the diction used in a text. This factor includes the use of new words, foreign words and ambiguous words. The second one is related to sentences which a translator writes. This factor includes (1) the use of foreign sentences, ambiguous sentences and incomplete sentences, (2) the length of the sentences and (3) the complexity of the sentences. The next factor is how the translator arranges the idea of his or her translation. The last factor includes other factors than which have been mentioned. They are (1) the content of a text, (2) the appearance of a text and (3) the ability of both the translator and the reader (Nababan: 2003).

xxxiii F. Friendster

Friendster is an online social networking service. It was founded in

California by Jonathan Abrams in the year of 2002. Friendster is a privately owned internet social networking website and the first online social network.

Its headquarters are in Mountain View, CA, US. Friendster is one of the oldest and first of the popular social networking sites boom. The concept of friendster is based on a circle of friends and various friends’ techniques for individuals to social network within virtual communities. Friendster is focused on helping people meet new friends, stay in touch with old ones and sharing online content and media. The website is also used for dating and discovering new events, bands, hobbies, and more. Users can share content including videos, photos, messages and comments with friends via their profile and their network.

Friendster is widely used in Asia. It has over 50 million users worldwide.

MySpace took over Friendster's number one position in popular social networking sites when it was introduced in 2004. Now the social networking site known as friendster has competition from every angle. There are new social networking sites growing everyday. Averages of 90% of young people are participating in social networking sites daily. Google offered to buy the social network called

Friendster in the year of 2003 but Friendster declined. Today, that decision not to sell to Google is considered as one of the biggest financial mistakes to many individuals. The amount of 53 million was funded to Friendster by Kleiner

Perkins Caufield & Byers and Benchmark Capital in the year of 2003. Friendster

xxxiv was awarded the prestigious patent in the year of 2006 for their method of calculating and displaying relationships in a social network.

It was dubbed with the name of Web of Friends due to the circles displayed of individual friends profile pictures. Each circle has a line drawn similar to a web connecting them to another contact on your friend list. It was very creative and crafty of them. Friendster is available in many different languages. Friendster has a language link that can change the text displayed on the site to Chinese, Japanese, Korean, Thailand, Indonesia, or Spanish for other users.

(http://www.webupon.com/Social-Networks/The-History-of-Friendster.102940)

G. Website Localization

With the rise in ownership of computers and internet usage growing daily, the internet is fast becoming the primary port of call for information, shopping and services. In addition, those computer and internet users are increasingly from non-English speaking countries. At the end of 2002, it was estimated that 32% of internet users were non-native English speakers. This figure is constantly rising.

In response, businesses have quickly become aware of the benefits of website localization.

Website localization is the process of modifying an existing website to make it accessible, usable and culturally suitable to a target audience. Website localization is a multi-layered process needing both programming expertise and linguistic/cultural knowledge. If either is missing, the chances are that a localization project will encounter problems. In the majority of cases it is the lack

xxxv of linguistic and cultural input that lets a website localization project down. In order to give an insight into the impact culture has on website localization the following examples depict areas in which a solid understanding of the target culture is necessary.

Translating a website from English into another language is not as simple as it may appear. There are numerous factors that have to be taken into consideration when translating a websites’ content. One must analyze the style of the language and the target audience. If the audience is foreign business personnel, the vocabulary, grammar and punctuation must reflect this. If the audience is informal or youth orientated then a more relaxed language must used.

Just as we in the UK would identify the difference between a site using ‘posh

English’ and ‘street English’, other cultures will have the same perceptions of language. Using the wrong language for the wrong reader in your localization project will lead to a misunderstanding of the site or company.

It is essential to assess what information is necessary to carry over into the new site. Do not assume that all information on the English site is automatically transferred over. One must evaluate the target culture and society.

(http://ezinearticles.com/?Culture-and-Website-Localization&id=832)

xxxvi CHAPTER IV

DATA ANALYSIS

A. INTRODUCTION

Chapter four presents analysis data to answer the problem statements as mentioned in the chapter one. This chapter consists of two main parts. The first part is the introduction, which provides the illustration of what would be analyzed in this research. The second part is the analysis of the data.

First, the analysis deals with the techniques used by the translator in translating the friendster website. Then, the second analysis would be about the quality of the translation. It presents the analysis of the accuracy, acceptability, and readability of the translation. It would provide the findings of the research based on the questionnaires which were completed by the raters and respondents.

B. ANALYSIS

This section presents the techniques applied by the translator to translate the website in English version into Indonesian version. There are some techniques found in translating the website.

1. Translation Techniques

The first part of this chapter is analysis about the translation techniques that are used by the translator in translating the friendster.com. After analyzing all of the data in both texts, the researcher finds ten translation techniques used by the

xxxvii translator to translate text from source language into the target language. They are addition, borrowing, naturalization, literal, deletion, free, and structural shift from plural into singular, structural shift from modifier-head (M-H) into head-modifier

(H-M), unit shift from phrase into word, and unit shift from word into phrase.

1. 1. Addition.

Addition is a technique where the translator adds some information in the translation to give a clearer translation to the reader. There are 7 data that are translated using addition technique.

Example from the data:

Example 1: 076. Friend requests 076. Permintaan Menjadi Teman Example 2: 102. Newsletter updates 102. Pembaruan Buletin Berkala Example 3: 167. Current courses 167. Kelas yang diikuti saat ini

The examples above show that there are additions of some words. Those examples use addition translation technique for semantic reason, since the purpose of the addition is to make the translation more easily to be understood by the users. The translator put the addition words ‘menjadi’, ‘berkala’, and ‘yang diikuti’, within phrases of the examples. The additions of words, however, do not change the message.

xxxviii The data numbers of this technique can be seen in the table:

Table 4.1.1 Addition Technique Data numbers Total

Addition 048, 064, 076, 084, 102, 144, 167 7

1. 2. Borrowing or borrowing plus explanation.

In this technique, the translator transfers the words from the source language into the target language without any modification. This technique is usually used to translate specific terms, names, places, and scientific terms. The translator can borrow the SL words and give explanation about the borrowed words. There are 21 data that are translated using borrowing technique.

Example from the data: Example 1: 007. Email address 007. Alamat email Example 2: 119. Your URL 119. URL Anda Example 3: 152. Friendster skins 152. Skin friendster

From the examples above, it can be seen that the translator borrowed some words from the source language in the target language. The examples show that the translator borrowed the words ‘email’, ‘URL’, and ‘skin’. In this example, the

xxxix word ‘skin’ can be translated into “kulit” in the TL, but the users may not be familiar with the word “kulit”. It makes the translator prefers to keep the original word.

The data numbers of this technique can be seen in the table:

Table 4.1.2 Borrowing or borrowing plus explanation Technique Data numbers Total Borrowing or 007, 018, 056, 065, 070, 071, 072, 087, 094, borrowing 098, 101, 110, 114, 119, 125, 131, 147, 155, 21 plus 160, 163, 169 explanation

1. 3. Naturalization.

This technique succeeds transference and adapts the source language word, first to the normal pronunciation, then to the normal morphology of the target language. There are 33 data that are translated using naturalization technique.

Examples from the data:

Example 1: 022. NEW Bulletins 022. Buletin BARU Example 2: 027. NEW Horoscope 027. Horoskop BARU Example 3: 132. Zodiac sign 154. tanda zodiak

xl From the three examples above, it can be seen that the translator employed naturalization in translating some words. In the first example, the words

‘bulletins’, ‘horoscope’, and ‘zodiac’ are absorbed into Bahasa Indonesia as

“buletin”, “horoskop”, and “zodiak”. The ST words are adopted into Bahasa

Indonesia by changing some consonants of the source language words. To translate word “bulletin”, the consonants of double -l- are changed into one -l- to adjust the Indonesian language system. In the word ‘horoscope’ and ‘zodiac’, the consonant -c- is changed into -k-, also for the word ‘horoscope’, the last vowel –e is deleted.

The data numbers of this technique can be seen in the table:

Table 4.1.3 Naturalization Technique Data numbers Total 004, 019, 022, 027, 028, 039, 052, 058, 059, 060, 065, 079, 082, 083, 085, 089, 091, 097 Naturalization 33 099, 105, 106, 109, 112, 118, 125, 126, 127, 129, 132, 147, 148, 159, 162

1. 4. Literal Translation.

Literal translation is a translation that follows closely the form of the source text, known as word-for-word translation (Larson 1984:10). It focuses on the form and structure of the target text. It is a SL oriented translation technique.

There are 34 data that are translated using literal technique.

xli

Example from the data:

Example 1: 013. About us 013. Tentang kami Example 2: 017. Policy privacy 017. Kebijakan privasi Example 3: 093. Two degrees 093. Dua gelar

From those three examples, it can be seen clearly that the translator applies the literal technique by translating the phrases word for word and keep the structure of sentence of the SL.

The data numbers of this technique can be seen in the table:

Table 4.1.4 Literal Technique Data numbers Total 002, 012, 013, 014, 017, 018, 028, 032, 036, 040, 042, 043, 044, 046, 049, 059, 113, 115, Literal 34 117, 118, 120, 133, 134, 135, 138, 141, 142, 143, 153, 154, 157, 161, 166

1. 5. Free Translation

Free translation is translation technique that places meaning as the highest priority. It means that the translator task is to deliver meaning the same as the

xlii original although with very different structure and wording. There are 10 data that are translated using free translation technique.

Example from data:

Example 1: 016. Terms of service 016. Syarat dan layanan Example 2: 069. Maiden Name 069. Nama gadis Example 3: 167. Current courses 167. Kelas yang diikuti saat ini

Those three examples show that the translator uses free translation to translate the phrases. As seen in the example 1, the translator translates ‘terms of service’ freely into “Syarat dan Layanan” rather than “Ketentuan Layanan” which is the literal translation of ‘terms of service’. In the example 2, the translator translates ‘maiden’ freely into “gadis”. In the example 3, the translator translates ‘courses’ freely into “kelas”.

The data numbers of this technique can be seen in the table:

Table 4.1.5 Free Translation

Technique Data numbers Total Free 016, 017, 035, 037, 069, 090, 103, 106, 136, 10 Translation 166

xliii

1. 6. Translation Shifts.

This technique is used in order to overcome problems related to the different language system between SL and TL. Shift is a translation technique involving a change in the grammar from the source language into the target language. There are two types of shift found in the data, they are structure shifts and unit shifts.

a) Structure Shifts.

This type involves a grammatical change between the structure of the SL and TL. Catford (1965:77) states that this shift, in grammar, can occur at all rank; at group rank and at clause rank.

1. Shift from Plural into Singular.

This is the kind of shift that changes the structure of the word and phrase of the SL after being translated into TL from plural into singular. There are 35 data that are translated using this technique. Example 1: 022. NEW Bulletins 022. Buletin BARU Example 2: 123. LâmβânK's Friends 123. Teman dari LamBank Example 3: 129. Favorite musics 129. Musik favorit

xliv In the three examples above, some plural forms are changed into singular forms. In datum number 022 the translator changes the words ‘bulletins’ (plural) into “bulletin” (singular). The same case also happen in the data number 123 and

129 where the words ‘friends’ and ‘musics’ (plural) are translated into “teman” and “musik” rather than “teman-teman” and “music-music”, the plural forms in

Indonesian language.

2. Shift from Modifier - Head (M - H) into Head - Modifier (H - M).

This kind of translation shifts that change of the structure of phrase because of different system of grammar between SL and TL. There are 101 data that are translated using this technique. Example 1: 007. Email address à Alamat Email H M M H Example 2: 073. Continent List à Daftar Benua H M M H Example 3: 170. School name à Nama sekolah H M M H

Those examples of SL are phrases with modifiers ‘address’, ‘list’, and

‘name’, while the heads are ‘email’, ‘continent’, and ‘school’. The TL phrase structures are different in which the modifiers are “alamat”, “daftar”, and

“nama”, while the heads are “email”, “benua”, and “sekolah”. The example above shows the structural shift at the group rank. The structure of English noun

xlv phrase will automatically change if it is translated into Indonesian as shown in the example above.

The three examples above show that the position of adjective is changed.

In English structure, adjective functions as modifier, so its position must be in front of the head. It is different from the structure of Bahasa Indonesia where adjective must be preceded by noun. Thus, the translation of email address, continent list, and school name (M-H) are alamat email, daftar benua, and nama sekolah (H-M).

b) Unit Shifts.

This type of translation shift involves change in rank. As stated by Catford

(1965:79) that unit shift occurs when the translation equivalent of a unit at one rank in the SL is a member of a different rank in the TL.

1. Shift from word into phrase.

This is the kind of shift that changes the rank from word into phrase. There are 11 data that are translated using this technique. Example 1: 053. College search 113. Pencarian perguruan tinggi Example 2: 113. More searches 113. Lebih banyak pencarian

In datum number 053, it can be seen that the word ‘college’ is translated into a phrase “perguruan tinggi”. The occurrence of this technique can

xlvi also be seen in datum number 113 where the word ‘more’ is translated into “lebih banyak”.

Table 4.1.6 Translation Shift

Technique Data numbers Total Shift from 002, 005, 009, 020, 022, 023, 024, Structure plural into 025, 031, 038, 041, 045, 048, 058, 061, 065, 066, 067, 076, 077, 083, 35 Shifts singular 092, 094, 096, 097, 099, 100, 101, 102, 122, 123, 125, 127, 134, 150

xlvii 001, 003, 004, 005, 006, 007, 008, 009, 010, 011, 015, 019, 020, 022, 023, 024, 025, 026, 027, 029, 030, 031, 033, 034, 035, 037, 038, 039, 041, 045, 047, 048, 050, 051, 052, 053, 054, 055, 056, 057, 058, 060, 061, 062, 065, 066, 067, 068, 070, 071, 072, 073, 074, 075, 076, 077, 078, 079, 080, 081, 082, 083, 084, Shift from (M- 085, 086, 087, 088, 089, 090, 091, 138 H) into (H-M) 092, 093, 094, 095, 096, 097, 098, 099, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 114, 116, 119, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 136, 137, 139, 140, 144, 145, 146, 147, 148, 149, 150, 155, 156, 158, 159, 160, 162, 163, 164, 165, 168, 169, 170, 171, 172 Shift from word Unit Shifts 021, 043, 053, 100, 113, 123, 135, into phrase 11 145, 146, 164, 165

Total 163

Here is the table that shows the complete distribution of translation techniques of the website friendster.com.

Table 4.1.7

xlviii Translation Techniques

Number No Techniques Percentage of data 1 Addition 7 2.76 % 2 Borrowing or borrowing plus explanation 21 7.24 % 3 Naturalization 33 11.38 % 4 Literal 34 11.72 % 5 Free Translation 10 3.45% 6 Structure Shifts: Shift from plural into singular 35 12.07 % Shift from (M-H) into (H-M) 138 47.59 % Unit Shifts: Shift from word into phrase 11 3.79 % Total 299 100%

The number of the data is more than 172 since most of the data are applied more than one technique.

From the research, it can be seen that translation techniques that is most frequently used by the translator is structure shift from (M-H) into (H-M). It has been used to translate 138 data or 47.59% from the overall data. It is followed by structure shift from plural into singular that has been used to translate 35 data or

12.07% from the overall data. It followed by literal translation that has been used to translate 34 data or 11.72% from the overall data, then naturalization with 33 data or 11.38% from the overall data. The next is borrowing or borrowing plus explanation with 21 data or 7.24% from the overall data, then unit shift from word into phrase 11 data or 3.79% from the overall data, free translation with 10 data or

3.45% from the overall data, , and addition with 7 data or 2.76% from the overall data.

xlix

2. Translation Quality Assessment

2.1. Accuracy

This section presents the analysis of the accuracy level of the translation of the website friendster.com.

The researcher involves three raters who have certain qualifications to assess the accuracy and the acceptability of the translation. The three raters were asked to complete the questionnaires to determine the accuracy and acceptability of the message transfer of the translation. The questionnaires are in form of close and open-ended questionnaire. In this form of questionnaires, firstly, the raters determine the accuracy of the translation by giving mark to the translation and then, secondly, they may give their comments or suggestions related to the accuracy of message transfer of the translation.

The accuracy of message transfer of the translation is measured based on the following scale:

Scale Description Accurate, the content of the original text is perfectly conveyed into 1 the target text. The translation is clear and no rewriting is needed. Less Accurate, the content of the original text is less perfectly conveyed into the target text. The translation can be clearly 2 understood, but some rewriting and some changes in word order are needed. Inaccurate, the content of the original texts is not perfectly conveyed 3 into the target text. There are some problems with the choice of lexical

l items and with the relationships between phrase and sentence elements. Very Inaccurate, the content of the original texts is not conveyed at 4 all, .e. it is omitted or deleted.

After the raters complete all of the questionnaires, the researcher makes statistical calculation to determine the mean of each datum with a formula.

Data Rater 1 Rater 2 Rater 3 Total Mean Number Total score 01 score score score total Total raters Total score 358 score score score total Total raters

When the statistical calculation is finished, the data are classified into four groups, as can be seen below:

1. Classification A: Accurate, includes the data with score mean 1.00.

2. Classification B: Less Accurate includes the data with score mean

1.01 – 2.00.

3. Classification C: Inaccurate, includes the data with score mean 2.01 –

3.99.

4. Classification D: Very Inaccurate includes the data with score mean

4.00.

Based on the table of accuracy in appendix, of 172 data, 146 data (84.88%) were categorized in classification A or accurate, 26 data (15.12%) were

li categorized in classification B or less accurate, with no data that was categorized in classification C or inaccurate and D or very inaccurate.

Mean of all data = : total data

= : 176

= 1.07 (B)

It means that equally, the accuracy level of the website is B / Less accurate.

Table 4.2.1

The table distribution of accuracy level:

Classification Data Number Total 001, 003, 004, 005, 006, 007, 008, 009, 010, 011, 012, 013, 014, 017, 018, 019, 020, 021, 022, 024, 025, 026, 027, 028, 029, 030, 031, 032, 034, 035, 036, 037, 038, 039, 040, 041, 042, 043, 044, 045, 046, 049, 050, 051, 054, 055, 056, 057, 058, 059, 060, 061, 063, 065, 066, 067, 068, 069, 070, 071, 072, 073, 075, 076, 077, 078, 079, 080, 083, 085, 086, 087, A 089, 090, 091, 092, 093, 094, 095, 096, 097, 146 098, 099, 100, 101, 102, 105, 106, 107, 110, 111, 112, 113, 114, 116, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 141, 142, 143, 144, 145, 146, 147, 148, 149, 151, 152, 153, 154, 155, 156, 157, 159, 160, 161, 162, 163, 164, 165, 167, 168, 169, 170, 171, 172 002, 015, 016, 023, 033, 047, 048, 052, 053, B 062, 064, 074, 081, 082, 084, 088, 103, 104, 26 108, 109, 115, 117, 139, 140, 150, 158 C 0 0

lii D 0 0

Total 172

1. Classification A: Accurate Translation.

All data classified in this classification are accurate. The mean score of the data is 1.00. There are 146 data (84.88%) considered to be accurate. It means content of original text is accurately conveyed and it does not need any rewriting.

Some of the data are presented below:

Example 1: 015. My blocked user 015. Pengguna saya yang diblokir Example 2: 093. Two degrees 093. Dua gelar Example 3: 116. Activity partners 116. Mitra aktivitas

Those three examples are considered to be accurate. All of the three raters gave score 1.00. Datum 015 applies structure shift from H–M into M–H translation technique. Datum number 093 applies structure shift from plural into singular translation technique. Datum 116 applies structure shift from H–M into

M–H and structure shift from plural into singular translation technique. The data are accurate according to three raters with the mean score 1.00 because the meaning of the sentences are accurately conveyed into the TL.

liii

2. Classification B: Less Accurate.

All data classified in this classification are less accurate. The mean score of the data is 1.01 into 2.00. There are 26 data (15.12%). The data are classified less accurate, if the content of original text is less accurately conveyed and some rewritings are needed.

Some of the data are presented below:

Example 1:

023. NEW Birthdays

023. Ulang Tahun BARU

Different judgment is given toward this translation. Both of two raters, rater 2 and 3, gave score 1, while the rater 1 gave score 2. The judgment result for this translation is 1.33 for the mean of translation. Rater 2 and rater 3 argue that the message of this text is accurately conveyed and it has appropriate meaning of the text. Different opinion proposed by rater 1. According to the rater 1, the message of the original text is not accurately conveyed.

Example 2:

139. Dating Men

139. Pria Berkencan

Different judgment was given toward this translation. All of three raters gave different opinion about the score of accuracy of this translation. Rater 1 gave score 3, rater 2 gave score 2, and rater 3 gave score 1. The judgment result for this translation is 2.00 for the mean of translation. Rater 1 argued that the message of

liv this text is inaccurately conveyed and it has appropriate meaning of the phrase.

Different opinion is proposed by rater 2 and rater 3. According to the rater 2, the accuracy level of this translation is less accurate, and the rater 3 argues that this translation is accurate. In addition, rater 1 and 2 mentioned that there is a rewriting needed. Rater 2 gave opinion that the phrase ‘dating men’ should be translated into “pria untuk teman berkencan”rather than “pria berkencan”. The researcher, then, agree with the rater 2’s opinion. It really needs a rewriting for this translation.

Example 3:

140. Dating Women

140. Wanita berkencan

Different judgment was given toward this translation. All of three raters gave different opinion about the score of accuracy of this translation. Rater 1 gave score 3, rater 2 gave score 2, and rater 3 gave score 1. The judgment result for this translation is 2.00 for the mean of translation. Rater 1 argued that the message of this text is inaccurately conveyed and it has appropriate meaning of the phrase.

Different opinion is proposed by rater 2 and rater 3. According to the rater 2, the accuracy level of this translation is less accurate, and the rater 3 argues that this translation is accurate. In addition, rater 1 and 2 mentioned that there is a rewriting needed. Rater 2 gave opinion that the phrase ‘dating women’ should be translated into “wanita untuk teman berkencan”rather than “wanita berkencan”.

2.2. Acceptability

lv This section presents the analysis of the acceptability level of the translation of the website of friendster.com. Acceptability means to produce translation which is natural according to target language system. A translator should express the message he or she translates appropriate with the literary norms of target language.

The norms include sentence structures, grammars, and dictions etc. Thus, to produce acceptable translations, a translator must express the transferred message in natural expressions in target language.

The acceptability of message transfer of the translation is measured based on the following scale:

Scale Description Acceptable, the translation sounds natural and appropriate with the 1 grammar structure of the target texts, almost does not feel like translation. Less Acceptable, the translated texts sound like translation. There are 2 some displeasing in terms of the words, phrases, and sentences in the target text, but almost sounds like natural. Inacceptable, the translated texts extremely sounds like translation 3 and feel displease as Indonesian texts.

After the raters complete all of the questionnaires, the researcher makes statistical calculation to determine the mean of each datum with a formula.

Data Rater 1 Rater 2 Rater 3 Total Mean Number Total score 01 score score score total Total raters Total score 358 score score score total Total raters

lvi

When the statistical calculation is finished, the data are classified into three groups, as can be seen below:

1. Classification A: Acceptable, includes the data with score mean 1.00

– 1.59.

2. Classification B: Less Acceptable includes the data with score mean

1.60 – 2.59.

3. Classification C: Inacceptable, includes the data with score mean 2.60

– 3.00.

Based on the table of acceptability in appendix, of 172 data, 157 data

(91.28%) were acceptable or in classification A, 15 data (8.72%) were less acceptable or in classification B, and there was no data classified as inacceptable or in classification C.

Mean of all data data = : total data

= : 172

= 1.20 (A)

It means that equally the acceptability level of the website is A /

Acceptable.

Table 4.2.2

The table distribution of acceptability level:

lvii Classification Data Number Total 002, 003, 004, 005, 006, 007, 008, 009, 010, 011, 012, 013, 014, 015, 016, 017, 018, 019, 020, 021, 022, 023, 024, 025, 026, 027, 028, 029, 030, 031, 032, 034, 035, 036, 037, 038, 039, 040, 043, 045, 046, 047, 048, 049, 050, 051, 052, 053, 054, 055, 056, 057, 058, 060, 061, 063, 064, 065, 066, 067, 068, 069, 070, 071, 072, 073, 074, 075, 076, 077, 078, 079, A 080, 081, 082, 083, 084, 085, 086, 087, 088, 157 089, 090, 091, 092, 093, 094, 095, 096, 097, 099, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 136, 137, 138, 141, 142, 143, 144, 145, 146, 147, 148, 149, 151, 153, 155, 156, 157, 158, 159, 160, 161, 163, 164, 165, 167, 168, 169, 170, 171, 172 033, 040, 041, 052, 074, 098, 123, 134, 135, 15 B 139, 140, 150, 152, 154, 162 C 0 0

Total 172

1. Classification A: Acceptable Translation.

All data classified in this classification are acceptable. The mean score of the data is from 1.00 – 1.59. There are 157 data (91.28%), considered to be acceptable. They are classified as acceptable translation since they sound natural and appropriate with the TL grammar, and do not feel like translation.

Some of the data are presented below:

Example 1:

061. My friends

061. Teman saya

Example 2:

lviii 068. Personal Information

068. Informasi pribadi

Example 3:

116. Activity Partners

116. Mitra aktivitas

Those three examples are phrases that are considered to be acceptable. All of three raters gave point 1.00 for those three examples. All of those examples apply structure shift from H – M into M - H that make the translation of those phrases become acceptable.

All of three raters agree that those sentences are acceptable. They gave score 1.00 for each phrase, and make the mean score become 1.00 that is acceptable according to the scale of acceptability.

2. Classification B: Less Acceptable Translation.

All data classified in this classification are acceptable. The mean score of the data is from 1.60 – 2.59. There are 15 data (8.72%). The data are considered less acceptable, if the translation sounds natural and appropriate with the grammar structure of the target texts, almost does not feel like translation.

Some of the data are presented below:

Example 1:

048. ias’s blogs

048. blog dari ias

lix Different judgment was given toward this translation. Three raters gave different opinion about the score of acceptability of this translation. Both rater 1 and 2 gave score 2, while the rater 3 gave score 1. The judgment result for this translation is 1.66 for the mean of translation. Rater 3 argued that the translation sounds natural and appropriate with the grammar structure of the target texts, it almost does not feel like translation. Different opinion proposed by rater 1 and rater 2. According to both the rater 1 and 2, the acceptability level of this translation is not acceptable. Both rater 1 and rater 2 argued that translated phrase sounds like translation. There is some displeasing in terms of the structure of phrase in the target text, but almost sounds like natural. Rater 1 and rater 2 argued that the translation of the phrase should be “blog ias”, the translator should delete the word “dari’ in order to make the translation sounds natural for the users in

TL.

Example 2:

098. Bookmark Updates

098. Pembaruan Bookmark

There was different judgment given toward this translation. Three raters gave different opinion about the score of acceptability of this translation. Both rater 1 and 3 gave score 2, while the rater 2 gave score 1. The judgment result for this translation is 1.66 for the mean of translation. According to rater 1 and 3, the acceptability level of this translation is less acceptable. Three raters argued that the translated phrase sounds like translation. There is some displeasing in terms of the structure of phrase in the target text, but almost sounds like natural. Rater 2

lx argued that that the translation of the phrase is acceptable because it sounds sounds natural for the users in TL.

Example 3:

123. ºLâmβânKº's Friends

123. teman dari LamBank

Different judgment was given toward this translation. Three raters gave different opinion about the score of acceptability of this translation. Rater 1 and rater 2 gave score 2, while the rater 3 gave score 1. The judgment result for this translation is 1.66 for the mean of translation. According to both the rater 1 and 2, the acceptability level of this translation is less acceptable. Both rater 1 and rater 2 argued that translated phrase sounds like translation. There is some displeasing in terms of the diction of the phrase in the target text, but almost sounds like natural.

According to the rater 2, argued the translation of the phrase should be “teman

LâmβânK's””. The researcher, then, agree with the opinion of rater 3. The translation of the phrase is acceptable and it sounds natural for the users in the TL.

2.3 Readability

This section presents the analysis of the readability level of the translation of the website of friendster.com.

The researcher involves eighteen respondents that willing to asses the readability of text. The eighteen respondents were asked to complete the questionnaires to determine the readability level of the translation. The questionnaires are in form of close questionnaire. In this form of questionnaires,

lxi respondents determine the readability of the translation by giving mark to the

translation.

The accuracy of message transfer of the translation is measured based on

the following scale:

Scale Description Easy to understand, the translation text can be understood after being 1 read in the first time. Less easy to understand, the translation text can be understood after 2 being read two or three times. Difficult to understand, the translation text can be understood after 3 being read in several times. Very difficult to understand, the translation text can not be 4 understood at all.

After all of the questionnaires are completed by the respondents, the

researcher makes statistical calculation to determine the mean of each datum with

a formula.

Data Respondent Respondent ….. ….. Total Mean Number 1 18 Total score 01 score score score score total Total respondents Total score 358 score score score score total Total respondents

When the statistical calculation is finished, the data are classified into four

groups, as can be seen below:

1. Classification A: Readable, includes the data with score mean 1.00.

lxii 2. Classification B: Less Readable includes the data with score mean

1.01 – 2.00.

3. Classification C: Unreadable, includes the data with score mean

2.01 – 3.99.

4. Classification D: Very Unreadable includes the data with score

mean 4.00.

Based on the table of readability in appendix, of 172 data, 5 data (2.91%) were readable or in classification A, 101 data (58.72%) were less readable or in classification B, and 66 data (38.37%) were unreadable or in classification C, and there was no very inaccurate datum.

Table 4.2.3

The table distribution of readability level:

Classification Data Number Total

A 007, 010, 011, 012, 020 5 001, 002, 003, 004, 005, 008, 009, 013, 014, 015, 018, 019, 021, 023, 025, 026, 030, 033, 036, 038, 043, 044, 045, 046, 047, 048, 051, 053, 054, 055, 057, 058, 059, 061, 062, 063, 064, 065, 068, 069, 070, 072, 073, 075, 076, B 077, 079, 081, 083, 084, 086, 087, 089, 090, 101 092, 095, 096, 101, 103, 108, 109, 111, 112, 113, 114, 117, 122, 124, 125, 127, 128, 129, 130, 131, 132, 133, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 157, 158, 159, 161, 164, 165, 167, 168, 169, 170, 172 006, 016, 017, 022, 024, 025, 027, 029, 031, 032, 034, 035, 037, 039, 040, 041, 042, 050, C 052, 056, 060, 066, 067, 071, 074, 078, 080, 66 082, 085, 088, 091, 093, 094, 097, 098, 099, 100, 102, 104, 105, 106, 107, 110, 115, 116,

lxiii 118, 119, 120, 121, 123, 126, 134, 135, 148, 149, 150, 151, 152, 153, 154, 155, 156, 160, 162, 163, 171 D 0 0

Total 213

Mean of all data = : total data

= : 172

= 1.83 (B)

It means that equally the acceptability level of the website is B / Less

Readable.

1. Classification A: Readable Translation.

All data classified in this classification are readable. The mean score of the data is 1.00. There are 5 data (2.91%) considered readable. The data if the translation text can be understood after being read in the first time. The data are classified as readable translation since the readers can understand them after being read once.

Some of the data are presented below:

Example 1:

010. First name.

lxiv 010. Nama depan.

Example 2:

012. Date of birth.

012. Tanggal lahir.

Example 3:

020. NEW Messages.

020. Pesan BARU.

Those three examples are classified as readable translation. All of respondents gave score 1.00 to those examples. Example 1 is datum number 010.

It applies the transposition from H – M into M – H technique. It has the same technique with datum number 020. Both phrases are readable according to the respondents because the meaning in the TL can be understood after being read one time. The example 2 is datum number 012, it applies literal translation by translating the phrases word-for-word, but it is readable according to the respondents because they are familiar with the translation of the phrase.

2. Classification B: Less Readable Translation.

All data classified in this classification are less readable. The mean score of the data is in the range from 1.01 – 2.00. There are 101 data (58.72%). The data are classified less readable since translation can be understood after being read twice.

Some of the data are presented below:

Example 1:

lxv 024. NEW App Invitations

024. Undangan Aplikasi BARU

Different judgment was given toward this translation. This example is datum number 024. The eighteen respondents had different opinion about the readability level of this sentence. There are two respondents who gave score 4, three respondents who gave score 3, three respondents who gave score 2, and ten respondents gave score 1. The reader is confusing with the definition of ‘app invitations’. They need to open the website in order to know the actual definition of ‘app invitations’ itself. It means that the acceptability level of the phrase is less acceptable

Example 2:

075. Manually Accept Request

075. Terima Permintaan Secara Manual

Different judgment was given toward this translation. This example is datum number 075. The eighteen respondents had different opinion about the readability level of this sentence. There are one respondent who gave score 4, four respondents who gave score 3, six respondents who gave score 2, and seven respondents who gave score 1. The reader is confusing with the definition of

‘request’. They need to open the website in order to know the actual definition of

‘request’ itself. It means that the acceptability level of the phrase is less acceptable.

Example 3:

140. Dating Women

140. Wanita Berkencan

lxvi Different judgment was given toward this translation. This example is datum number 140. The eighteen respondents had different opinion about the readability level of this sentence. There are one respondent gave score 4, five respondents gave score 3, five respondents gave score 2, and seven respondents gave score 1. The judgment result for this translation is 2.00 for the mean of translation. There is inappropriate diction that makes the translation less readable.

The respondents argue that they could understand the phrase after reading twice, and what makes them difficult to understand the phrase is the word of

“berkencan”. The researcher, then, argues that the translation of the word

‘dating’ should be “sedang berkencan”.

3. Classification C: Unreadable Translation.

All data classified in this classification are unreadable. The mean score of the data is in the range from 2.01 – 3.99. There are 66 data (38.37%). The data are classified unreadable since the translation can be understood after being read several times.

Some of the data are presented below:

Example 1:

093. two degrees

093. dua gelar

Different judgment was given toward this translation. This example is datum number 093. The eighteen respondents had different opinion about the

lxvii readability level of this sentence. Two respondents gave score 4, six respondents gave score 3, five respondents gave score 2, and five respondents gave score

1.The judgment result for this translation is 2.27 for the mean of translation. There is inappropriate diction that is used by the translator in this phrase. The translator does not translate the word ‘degrees’ into the correct translation. The translator should translate ‘degrees’ into “tingkat”.

Example 2:

094. Email Notifications

094. Pemberitahuan Email.

Different judgment was given toward this translation. This example is datum number 094. The respondents had different opinion about the readability level of this sentence. Two respondent gave score 4, five respondents gave score

3, four respondents gave score 2, seven respondents gave score 1. The mean score for this translation is 2.27. The respondents are difficult to understand the meaning of the translation phrase because there is a word that still unfamiliar for the respondents.

Example 3:

119. Your URL

119. URL Anda

Different judgment was given toward this translation. This example is datum number 119. Four respondents gave score 4, seven respondents gave score

3, six respondents gave score 2, and 1 respondent gave score 1. The mean score for this translation is 2.77. The respondents are difficult to understand the

lxviii meaning of the translation phrase because there is a word that still unfamiliar for the respondents. Even, after accessing the website they still need more time to understand what actually the definition of the ‘URL’.

C. DISCUSION

This section presents the discussion about the result of the analysis about the translation techniques, the accuracy level, the acceptability level, and the readability level of the translation of the website of friendster.com.

The result of the analysis of this research is summarized in the following table:

Table 4.2.4

The Techniques and the Level of Accuracy, Acceptability, and Readability

Translation Number Translation Quality Assessments Percentage Techniques of Data Addition Accurate 5 71.43 % (7 data) Less Accurate 2 28.57 % Accuracy Inaccurate 0 0 % Very Inaccurate 0 0 % Acceptable 7 100 % Acceptability Less Acceptable 0 0 % Inacceptable 0 0% Readability Readable 0 0 % Less Readable 6 85.71 % Unreadable 1 14.29 %

lxix Very Unreadable 0 0 % Accurate 21 100 % Less Accurate 0 0 % Accuracy Inaccurate 0 0 % Very Inaccurate 0 0 % Acceptable 20 95.24 % Borrowing Acceptability Less Acceptable 1 4.76 % (21 data) Inacceptable 0 0 % Readable 1 4.77 % Less Readable 12 57.14 % Readability Unreadable 8 38.09% Very Unreadable 0 0 % Accurate 30 90.90 % Less Accurate 3 9.10 % Accuracy Inaccurate 0 0 % Very Inaccurate 0 0 % Acceptable 31 93.94 % Naturalization Acceptability Less Acceptable 2 6.06 % (33 data) Inacceptable 0 0 % Readable 0 0 % Less Readable 18 54.55 % Readability Unreadable 5 45.45 % Very Unreadable 0 0 % Literal Accurate 32 94.12 % Translation Less Accurate 2 5.88 % (34 data) Accuracy Inaccurate 0 0 % Very Inaccurate 0 0 % Acceptable 30 88.24 % Acceptability Less Acceptable 4 11.76 % Inacceptable 0 0 % Readability Readable 1 1.78 %

lxx Less Readable 24 70.59 % Unreadable 9 26.47 % Very Unreadable 0 0 % Accurate 8 80 % Less Accurate 2 20 % Accuracy Inaccurate 0 0 % Very Inaccurate 0 0 % Acceptable 10 100 % Free Translation Acceptability Less Acceptable 0 0 % (10 data) Inacceptable 0 0 % Readable 0 0 % Less Readable 5 50 % Readability Unreadable 5 50 % Very Unreadable 0 0 % Accurate 31 88.57 % Less Accurate 4 11.43 % Accuracy Inaccurate 0 0 % Very Inaccurate 0 0 % Structure Shift Acceptable 31 88.27 % From Plural Acceptability Less Acceptable 4 11.43 % into Singular (35 data) Inacceptable 0 0 % Readable 1 2.85 % Less Readable 22 62.86 % Readability Unreadable 12 34.29 % Very Unreadable 0 0 % Accurate 117 88.12 % Structure Shift Less Accurate 21 15.22 % From Head – Accuracy Modifier into Inaccurate 0 0 % Modifier – Head Very Inaccurate 0 0 % (138 data) Acceptability Acceptable 128 92.75 % Less Acceptable 10 7.25 %

lxxi Inacceptable 0 0 % Readable 3 1.45 % Less Readable 84 60.87 % Readability Unreadable 52 37.68 % Very Unreadable 0 0 % Accurate 10 90.90 % Less Accurate 1 10.10 % Accuracy Inaccurate 0 0 % Very Inaccurate 0 0 % Unit Shift from Acceptable 9 81.18 % Word into Acceptability Less Acceptable 2 18.18 % Phrase (11 data) Inacceptable 0 0 % Readable 0 0 % Less Readable 8 72.73 % Readability Unreadable 3 27.27 % Very Unreadable 0 0 %

The result of data analysis shows that the data are classified into 8

categories based on the translation techniques involved. The technique that is

most frequently used is structure shift from (M-H) into (H-M). There are 138 data

or 47.59% from the overall data. Among 138 data, 117 data are considered to be

accurate translation, 21 data are considered to be less accurate translation. There

are 128 data are considered to be acceptable translation, 10 data are considered to

be less acceptable translation, among 138 data, 3 data are considered to be

readable translation, 84 data are considered to be less readable translation, and 52

data are considered as unreadable translation. In other words, majority of the data

translated by using structure shift from (M-H) into (H-M) tend to be accurate,

acceptable, but less readable.

lxxii The following technique is structure shift from plural into singular. There are 35 data identified as this translation technique or 12.07% from total the overall data. Among 35 data, 31 data are considered to be accurate translation, 4 data are considered to be less accurate translation. There are 31 data are considered to be acceptable translation, 4 data are considered to be less acceptable translation. In addition, among 35 data, 1 datum is considered to be readable translation, 22 data are considered to be less readable translation, and 12 data are considered as unreadable translation. In other words, majority of the data translated by using structure shift from plural into singular tend to be accurate, acceptable, but less readable.

The following technique is literal translation. There are 34 data or 11..72% from the overall data. Among 34 data, 32 data are considered to be accurate translation, 2 data are considered to be less accurate translation. There are 30 data considered to be acceptable translation, 4 data are considered to be less acceptable translation. In addition, among 34 data, 1 datum is considered to be readable translation, 24 data are considered to be less readable translation, and 9 data are considered as unreadable translation. In other words, majority of the data translated by using literal translation technique tend to be accurate, acceptable, but less readable.

The next classification is naturalization. There are 33 data classified in this category or 11.38% from the overall data. Among 33 data, 30 data are considered to be accurate translation, 3 data are considered to be less accurate translation.

There are 31 data are considered to be acceptable translation, 2 data are

lxxiii considered to be less acceptable translation. In addition, among 33 data, 18 data are considered to be less readable translation, and 15 data are considered as unreadable translation. In other words, majority of the data translated by using naturalization technique tend to be accurate, acceptable, but less readable.

The next category is borrowing or borrowing plus explanation with 21 data include in this category or 7.24% from total of translation technique used. Among

21 data, 21 data are considered to be accurate translation. There are 20 data are considered to be acceptable translation, 1 datum is considered to be less acceptable translation. In addition, among 21 data, 1 datum is considered to be readable translation, 12 data are considered to be less readable translation, and 8 data are considered as unreadable translation. In other words, majority of the data translated by using borrowing or borrowing plus explanation technique tend to be accurate, acceptable, but less readable.

The next category is unit shift from word into phrase with 11 data or

3.79% from the overall data. Among 11 data, 10 data are considered to be accurate translation, 1 datum is considered to be less accurate translation. There are 9 data are considered to be acceptable translation and 2 data are considered to be less acceptable. In addition, among 11 data, 8 data is considered to be less readable translation, 3 data are considered to be unreadable translation. In other words, majority of the data translated by using addition technique tend to be accurate, acceptable, but less readable.

The further technique used in translation of the friendster website is free translation with 10 data or 3.45% from the overall data. Among 10 data, 8 data are

lxxiv considered to be accurate translation and 2 datum are considered to be less accurate. There are 10 data are considered to be acceptable translation. In addition, among 10 data, 5 datum are considered to be less readable translation, 5 datum are considered to be unreadable translation. In other words, majority of the data translated by using addition translation technique tend to be accurate, acceptable.

The last category is addition 7 data or 2.76% from the overall data. Among

7 data, 5 datum is considered to be accurate translation, 2 data are considered to be less accurate translation. There are 7 data are considered to be acceptable translation. In addition, among 7 data, 6 data are considered to be less readable translation, 1 datum is considered to be unreadable translation. In other words, majority of the data translated by using unit shift from word into phrase technique tend to be accurate, acceptable.

ACCURACY

From the analysis of the questionnaire spread to three raters, the researcher found out that most of the translations are accurate with 172 data. In this case, accurate translation is the data that the average point range 1.00. The most frequent score given to the data is 1.00. The correct transfer of the content of the source text defines the accuracy of the translation importantly. In addition to be considered accurate, a translated text must be clearly understood and does not need any rewriting.

lxxv Although most of the data are included in accurate translation, it cannot be inferred that the translation of the website is good quality. The reason is that there are 26 data that are less accurate if it is seen from the transfer of the source text content. Each rater has their own consideration in giving scores to each of the data, but the researcher has set the scoring system to rate the accuracy level of the translation. Thus, the average score given by the raters can be used as a pointer for the accuracy level. Moreover, the raters are all experienced in translation theory, practice, and having competence in both English and Indonesian language. In general, the accuracy level translation of the friendster website is accurate.

ACCEPTABILITY

From the analysis of the questionnaire spread to three raters, the researcher found out that most of the translations are acceptable with 172 data. The acceptability of the translation is defined importantly by the natural sounds of translation and appropriate translation with the grammar structure of the target texts. In addition to be considered acceptable, a translated text must sound natural and appropriate with the grammar structure of the target texts.

Although most of the data are included in acceptable translation, it cannot be inferred that the translation of the website is high quality. The reason is because there are 15 data that are less acceptable if it is seen from the transfer of the source text content. Each rater has their own consideration in giving scores to each of the data, but the researcher has set the scoring system to rate the acceptability level of the translation. Thus, the average score given by the raters

lxxvi can be used as a pointer for the accuracy level. Moreover, the raters are all experienced in translation theory and practice and having competence in both

English and Indonesian language. In general, the acceptability level of translation of the friendster website is acceptable.

READABILITY

The readability of the translation is defined importantly by the understandability of texts to the target text users. In addition to be considered readable, a translated text must be understood after being read only 1 time. From the analysis of the questionnaire spread to 18 respondents, the researcher found out that most of the translations are less readable with 101 data. In this case, readability translation is the data that the average point range 1.01 – 2.00.

There are 66 data that are unreadable. Moreover, although in the smallest number, there is only 5 data that is classified as readable translation. Each respondent has their own consideration in giving scores to each data based on their ability in understanding the data, and the researcher has set the scoring system to rate the readability level of the translation. Thus, the average score given by the respondents can be used as a pointer for the accuracy level. In general, the readability level of translation of the friendster website is less readable.

lxxvii

CHAPTER V

CONCLUSION AND RECOMMENDATION

A. Conclusion

After the data analysis has been completed, the researcher draws some conclusions based on the problem statements and the results of the data analysis.

The conclusions are as follows:

1. The translation techniques used by the translator in translating the phrases of friendster.com are structure shift from (M-H) into (H-M) (138 data or

47.59%), structure shift from plural into singular (35 data or 12.07%), literal translation (34 data or 11.72%), naturalization (33 data or 11.38%), borrowing or borrowing plus explanation (21 data or 7.24%), unit shift from word into phrase

(11 data or 3.79%) free translation (10 data or 23.45%), and addition (74 data or

2.76%).

2. The analysis on translation accuracy shows that there are 146 data

(84.88%) considered to be accurate translation with classification A. There 26 data (15.12%) considered to be less accurate with classification B. The techniques result in high level of accuracy is structure shift from (M-H) into (H-M) with 117 data. The techniques result in low level of accuracy is addition with 5 data.

The analysis on translation acceptability shows that there are 157 data

(91.28%) considered to be acceptable translation with classification A. There are

15 data (8.72%) considered to be less acceptable with classification B. The

lxxviii techniques results in high level of acceptability are structure shift from (M-H) into

(H-M) with 128 data. The technique result in low level of acceptability is unit shift from word into phrase with 9 data.

The analysis on translation readability shows that there are 5 data (2.91%) considered to be readable translation with classification A. There are 101 data

(58.72%) considered to be less readable with classification B. There are 66 data

(38.37%) considered to be unreadable translation with classification C. The technique result in high level of readability is structure shift from Head – Modifier into Modifier – Head with 3 data. The techniques results in low level of readability are addition, naturalization, free translation, and unit shift from word into phrase with 0 data.

B. Recommendation

Regarding the result of the research, the researcher suggests several recommendations to:

1. English Department Students

The researcher expects that the result of the research could be

advantageous as one of the informational source to enlarge and sharpen

knowledge for the English department students, especially for those who

are studying translation of the translation, as an additional input and

reference to enlarge their knowledge of translation especially translation of

website.

lxxix 2. The Friendster.com Translator

The translator of the friendster.com should be aware that there are always

differences of the source language and the target language, grammatically,

either semantically, or stylistically. Therefore, the translator should be able

to choose and apply the proper technique to produce a good translation for

the improvement of the website quality.

3. Other Researchers

The result of this study could be used as a reference by other researchers to

conduct a further research related to the website translation quality

assessment.

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www.friendster.com Due date: December 23, 2009 at 12:26 pm www.webupon.com/Social-Networks/The-History-of-Friendster.102940 Due date: January 12, 2009 at 9:51 am www.erudit.org/revue/meta/2000/v45/n3/001878ar.pdf www.emanueltov.info/docs/papers/16.trans.techn.1999.pdf www.sportsci.org/jour/0001/wghdesign.htm www.southalabama.edu/coe/bset/johnson/lectures/lec14.htm http://ezinearticles.com/?Culture-and-Website-Localization&id=832 Due date: January 12, 2009 at 10:03 am www.geocities.com

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