Indonesian User Perception on the Usefulness of Auto-translate Feature on Social Media (original) (raw)

An English Oblique Translation Analysis of “Twitter” Social Networking Website into Indonesian: An Applied Linguistics Study

International and Public Affairs, 2019

The objective of this research is to analyze and find out the oblique translation through the terms and sentences from English version into Indonesian version. Social media like Twitter is one of many media that are used by people to communicate for near or far direction. To be able to use the media, translation is needed in order to have a good understanding in communication. Since its importance, this research is conducted in order to analyze a translation from one social networking website, twitter, which is served into bilingual version, English and Indonesian. The data is analyzed through a translation theory stated by Vinay and Darbelnet. The theory divides the method of translation into 2 main parts, (1) literal or direct translation which covers borrowing, calque, and literal translation. Meanwhile (2) an oblique translation, which is also called as translation procedures, serves transposition, modulation, equivalence, and adaptation. The research method in this research used is qualitative description. The data are taken from each sentence written in English (as Source Language/SL) into Indonesian (as Target Language/TL). After describing a translation theory about definition and translation procedures, it can be concluded that all procedures (oblique translation) are used and found in one social networking service, twitter. They are transposition, modulation, equivalence, and adaptation.

The Accuracy and Shortcomings of Google Translate Translating English Sentences to Indonesian

Education Quarterly Reviews, 2020

Google Translate is a free and practical online translation service that allows millions of people around the globe to translate words, phrases, sentences, and paragraphs into an intended target language. However, in 2015, some Google Translate users in Indonesia, filed complaints, asserting that the machine was often inaccurate, speculating that it could only translate languages at the micro-level of words and phrases, rather than complete sentences or paragraphs. This research works to examine the accuracy as well as the shortcomings of Google Translate, in the context of English to Indonesian translations, in order to critically engage the complaints made by Google users. For the purpose of this study, 80 English sentences were translated using Google Translate and assessed for accuracy using a table adapted from Memsource criteria. Both the original sentences and their translated versions were analyzed using a sentence pair matrix to determine the machine’s failings and areas fo...

ANALYSIS ON CLARITY AND CORRECTNESS OF GOOGLE TRANSLATE IN TRANSLATING AN INDONESIAN ARTICLE INTO ENGLISH

International Journal of Humanity Studies (IJHS), 2021

The objective of this study is to analyze the aspects of clarity and correctness in Google Translate's ability in translating an Indonesian article from English into Indonesian. This research refers to qualitative research. Data used in this research is a published Indonesian article which is translated into English by using Google Translate. Based on the analysis, the researcher concludes that Google Translate is a machine translator, but there is always going to be potentially less clarity and correctness at the end of the translation product such as in Indonesian articles into English. Because English grammar is a complicated thing to be learned, people perhaps cannot expect more that machine translator understands every aspect of the way human beings communicate with each other. That is why the answer about the clarity and the correctness of Google Translate is that it still has a way to go before it can consistently, clearly, and correctly translate the language without errors. In the clarity aspect, there is still no clarity in English translation by Google Translate, even it translated the language word-for-word. In the correctness aspect, it refers to the mechanical rule in writing which is related to grammar, punctuation, and spelling. Some examples of non-correctness are related to grammar and punctuation errors. Machine translators have come a long way in a short amount of time, but some features still lack good translation such as in aspects of grammar and punctuation.

Instagram Translation Machine: Does It Help Arabic Students to Know Arabic-Indonesian Translation Well?

LISANIA: Journal of Arabic Education and Literature

In recent decades, Instagram has launched a translation feature to help its user understand the caption in every Instagram posts. Its presence also has an impact on its users, including Arabic students. The purpose of this study is to identify the students’ perceptions about the use of these features and to know its impact on their understanding. The data collection technique was carried out in two different stages using a screening model. We distributed questionnaires to 24 Arabic students at Indonesia University of Education to find out the students' experiences while using this feature. The findings show that this feature is convenient, and the translations are quite understandable, but it is not uncommon for them to find translations that do not fit the context because this feature can produce good translations if the source language use the standard language. Most of the students also admitted that this feature affected their insight about translation. It can be used as an ...

AN ANALYSIS OF INDONESIAN-ENGLISH TRANSLATION USING FACEBOOK MACHINE TRANSLATION

2019

This study aims to analyze the quality of translation text of Facebook Machine Translation (MT). Facebook claims that their MT performs better than any other MT. This study uses the Mireia, et al. (2010) error classification scheme model which suggests a classification scheme with a clear linguistic categorization at the first level: orthographic, morphological, lexical, semantic, and syntactic errors. This study uses descriptive qualitative research method to analyze the data. The writer found that most of the errors are lexical error which are missing word, untranslated word and mistranslation, and semantic error which about coherency. In conclusion, manual translation is still needed for a good quality of translation, while MT is good for translating many text in an instant way, but the quality is not good.

Translation Analysis: The Quality of Translationresult of English Text Into Indonesian by Using“Google Translate”

2012

AHMAD ROBANI : TRANSLATION ANALYSIS THE QUALITY OF TRANSLATION RESULT OF ENGLISH TEXT INTO INDONESIAN BY USING GOOGLE TRANSLATE Today, internet allows all people to access information from all over the world anytime and anywhere. One tool that helps Internet users to search information effectively is “Google”. Currently, “Google” offers many applications, one of application is “Google Translate”. The “Google” developers realized that the information presented on a web page in Internet can be in various languages. Language can be a barrier for people to be able to understand the information if they did not mastering the language. Machine translation from “Google” is the solution. Currently, “Google Translate” can translate into more than 50 languages in the world. But, almost people did not know the quality of translation result when they use it. So, in this research, the investigation aims to investigate the quality of translation result from “Google Translate” and find what transla...

A Study of Google Translate Translations: An Error Analysis of Indonesian-to-English Texts

2019

Nowadays, internet technology allows everyone to access information from all corners of the world anytime and anywhere. One of the tool that helps internet users to find information effectively is Google. Google currently offers a variety of applications, one of which is Google-Translate. Google-Translate is used to translate from the source language to the target language. However, the results of the translation are often inappropriate or have some errors. The error analysis always occurs in grammar and selection of inappropriate words. Therefore, the objective of this research is to find out whether there are translation errors and to find out the types of translation errors that occur in the translation results in Kompas.com news text. The data analyzed are the news text of Kompas.com in Indonesian translates into English by Google-Translate. This study used thedescriptive qualitative method. To examine the validity of this research the researchers use triangulation. From the dat...

Students' Perceptions in Using The Google Translate Application to Translate Text from Indonesian Language into English Language

Scientific Writing, 2019

Google translate is an application used to translate the words of the mother language to the target language. Indonesia including most countries that use google translate application. Google translate application widely used in almost all human circles. Past research has proved that the use google translate application can be easier to use than the printed dictionary. The purpose of this study to determine students' perceptions about the use google translate application of the printed dictionary. This research was conducted in order to find out the reasons of using applications as well as the advantages and disadvantages of the application. The research data was collected from several classes with random method. Based on previous research on google translate, google translate namely that the application easier to use, simple and practical. Can also be used offline if you have close Downloading translation packages in the desired language.

Reader's Reactions on the Indonesian Online News Translation

2019

Nowadays online news articles might be said to be the basis of communication as they are the main source which delivers most up-to-date news on social life, culture, politics, etc. to the audience. Since cultural diversity and identity are the issues of modern cultures and societies, online media texts need to be analyzed, especially from the perspective of translation. This paper discusses the reader’s reaction in relation to their responses to reading translated news to Indonesia. This study uses qualitative approach to describe the results of the analysis of reader’s reaction in reading translated news to Indonesia. From the analysis conducted by the researchers, it can be seen that reader’s reaction indicated that the text is translated

A study into the motivations of internet users contributing to translation crowdsourcing: the case of Polish Facebook user-translators

Dombek Magdalena a Study into the Motivations of Internet Users Contributing to Translation Crowdsourcing the Case of Polish Facebook User Translators Phd Thesis Dublin City University, 2014

This section lists and defines the key terms associated with the translation crowdsourcing initiative as organised by Facebook and used in the thesis; the definitions have been provided by the researcher. award-a graphic object in the form of an emblem which is displayed on a user-translator's translator profile page on Facebook. Awards are offered for specific achievements in contribution to the translation initiative on Facebook. As translator profile pages are private, other usertranslators cannot see the awards collected by others in their community of user-translators. glossary-a list of words and phrases recognised as terms and translated by the user-translators. Suggestions from the glossary are displayed below the string currently being translated by a usertranslator. Upon clicking on the selected suggestion, it is automatically inserted into the translation at the point indicated by the user-translator. in-line editing-a mode for translation and voting on Facebook which allows these translation actions to be performed while using Facebook for day-today activities, as opposed to launching the collaborative translation platform. When in-line editing mode is switched on, Facebook text content which requires translation or is subject to voting will be underlined in red. A translation or a vote is submitted in a pop-up window displayed once the underlined segment is right-clicked. input module-the module which provides a user interface for the display of source phrases which need to be translated into a given target language. It also receives translations from Facebook user-translators. leaderboard-a ranking chart of Facebook user-translators who are listed depending either on the value and amount of their contribution to the translation of Facebook in a specified period of time or on the overall impact of their contribution on the translation initiative in their particular language. style guide-a set of stylistic guidelines written for a particular language by a member of the corresponding community of user-translators. The guide can be accessed at any time during translation. The style guide cannot be edited by the user-translators. token-a word or phrase in the original string which need not be translated, though has to be included in the string translation. A token is a placeholder for text with which it is replaced once xiv xiv the translated phrase is displayed to a Facebook user. A token may be used to avoid re-translation of a word or phrase for which a high-quality translation already exists. A token is displayed in curly brackets. tokeniser-an element which corresponds with the token included in the string a user-translator intends to translate. A tokeniser is displayed below the given source string and once clicked is automatically inserted into the translation at the point indicated by the user-translator. translation module-the module developed by Facebook to facilitate community translation of text phrases on the social networking website by the members of the website, i.e. Facebook users. The translation module consists of an identification module, an input module, a voting module, a weighting module and a presentation module which enable individual actions for translation on Facebook. translation suggestion-a translation of a particular string provided by one user-translator in the past and displayed to all the other user-translators working on the same string. A translation suggestion can be voted either up or down by the viewing user-translator; a user-translator can also edit the available suggestion and submit it as their new translation suggestion. Translations-a Facebook application in which the whole Facebook translation module is embedded. It needs to be installed to a user's Facebook profile to facilitate their participation in the translation activity on Facebook. The application provides access to the collaborative translation platform, leaderboards, glossary and style guide, and stores statistical information about one's progress in contribution to the initiative in their specified target language (received awards, number of provided translations, votes). Translator Community for Polski-a community of user-translators translating Facebook into Polish. The user-translators are not members of the community by default. They need to request group membership via the corresponding Polish Facebook translator community group page from the existing members or the Facebook Translation Team, who founded the community group. Translator Community for Polski is also the name of the dedicated Facebook Polish Translator Community group page. Translator Community group page-a Facebook group page operating as a communication channel for the Facebook user-translators. There is a separate group page for each of the languages in which Facebook is being translated. Depending on the target language set by a given user-translator, the corresponding group page is made available to them. By default, they can xv xv observe the activity in the group but cannot contribute to the discussions held in the group. To do this it is necessary to obtain group membership. variations-a mechanism which is part of the translation module on Facebook and which enables multiplication of a single original Facebook string so that a number of its variant translations can be submitted into the translation module. Variations are created to allow for differences in word forms constituting the translation and which depend on varying grammatical categories. votingmodule-the module which presents the user-translators with the source phrases and their translations, enables them to vote the translations up or down and stores these votes. weighting module-the module which assigns values to the votes received from the usertranslators and calculates quality of translations based on these votes.