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Kammer Sipayung
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Journal of English Language Teaching, Literatures, Applied Linguistics
Published by Merwinspy Publisher
ISSN : -     EISSN : 30258561     DOI : https://doi.org/10.69820/jeltlal.v1i1
Core Subject : Education,
Education Languange, Linguistic, Communication & Media
Focus Journal of English Language Teaching, Litterature and Applied Linguistics focuses on research related to English Language Pedagogy, TEFL English Teaching, English for Specific Purposes (ESP), ELT Materials Development and Evaluation, English Language Testing and Assessment, Linguistics, Literatture, Translation, Critical Discourse Analysis Research method approaches include: Quantitative, Qualitative, and Mix Method. JELTLAL has the following objectives: Provide a means of publication of empirical research and the field of teaching and applied linguistics. Disseminating the results of new scientific research in these field that can be applied as an alternative solution in the field of applied linguistics as well as teaching. Accelerate the transfer of knowledge from research to practice. Therefore, this journal contains empirical articles and critical reviews both using quantitative approaches (mainstream), qualitative approaches (alternative), and other methods. Scope Topics that can be published in this journal are topics related to Teaching language, Litterature and Applied Linguistics, such as: English Language Pedagogy, TEFL English Teaching English for Specific Purposes (ESP) ELT Materials Development and Evaluation English Language Testing and Assessment Linguistics Literatture Translation Critical Discourse Analysis
Arjuna Subject : Ilmu Sosial - Linguistik dan Bahasa
Articles 5 Documents
 1 
Search results for , issue "Vol. 3 No. 2 (2025): December" : 5 Documents clear
A Comparative Analysis of Translation Techniques between YouTube Subtitle Translation and the DeepL Translation Tool in the Song Lyrics of Shake It Off by Taylor Swift Limbong, Agneso Feronika; Situmorang, Haidah; Banjarnahor, Juliva Viona; Gultom, Aryadi Manuel
Journal of English Language Teaching, Literatures, Applied Linguistic (JELTLAL) Vol. 3 No. 2 (2025): December
Publisher : Merwinspy Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69820/jeltlal.v3i2.401

Abstract

This study uses a descriptive qualitative approach to examine the translation techniques used in the translated version of the song "Shake It Off" by Taylor Swift into Indonesian. The analysis compares two translations, namely the subtitle from YouTube (TT1) and the machine translation using the platform DeepL (TT2). This study refers to the framework of translation techniques developed by Molina and Albir (2002), as well as the interactive data analysis model of Miles and Huberman (1994) which includes the process of data condensation, data presentation, and conclusion drawing. The song lyrics were divided into units of analysis and arranged parallel to their respective translated versions to identify and classify the techniques used. The findings show that there is a significant difference in the application of translation strategies between TT1 and TT2. TT2 relies heavily on literal translation techniques (68 cases or 39.5%), reflecting the tendency to maintain the surface structure of the source text. In contrast, TT1 shows a higher diversity of techniques, especially adaptation (28 cases or 16.2%) and reduction (11 cases or 6.3%) techniques, reflecting the translator's sensitivity to the cultural context and audiovisual limitations. Other techniques such as amplification, borrowing and modulation also show variations in frequency of use between the two versions. In general, this study shows that human and machine interpreters have different priorities in conveying meaning, style and nuance in the context of translating song lyrics. These differences provide important insights into the advantages and limitations of each approach in the field of audiovisual translation.
Contrastive Analysis Of Idiom Translation: Literal vs. DeepL in Adele’s Song “Someone Like You” Into Indonesian Manullang, Yuni Maria; Damanik, Masta Artani; Simbolon, Diane Sarima Lestari; Gea, Sarah Nasrani; Sagala, Poster
Journal of English Language Teaching, Literatures, Applied Linguistic (JELTLAL) Vol. 3 No. 2 (2025): December
Publisher : Merwinspy Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69820/jeltlal.v3i2.405

Abstract

This study investigates the challenges and strategies involved in translating English idioms into Indonesian, with a particular focus on Adele's song "Someone Like You." The research employs a qualitative descriptive approach and utilizes contrastive analysis, with a focus on three quality indicators: accuracy, naturalness, and acceptability. The findings indicate that literal translation can result in statements that are either uncomfortable or incomprehensible in the target language, thereby leading to a loss of the intended meaning of the idiom. In contrast, the neural machine translation of DeepL demonstrated a significantly higher success rate, achieving an accuracy of 93.33% across the analyzed idioms. In comparison, the literal translation exhibited a substantially lower accuracy of 42.22%. This exemplifies the idiomatic fluency and contextual awareness of DeepL; nevertheless, human interaction remains imperative to preserve the emotional depth and cultural subtlety of literary texts. This research underscores the potential for a symbiotic relationship between technology and human aptitude, particularly in artistic domains such as music, where the translation of idioms can be particularly salient. Subsequent research endeavors may involve a more extensive investigation of idiom translation across genres and languages, with the objective of promoting the development of emotionally intelligent machine translation tools.
THE POLITENESS STRATEGY USED BY SHERLOCK HOLMES IN THE SIGN OF FOUR NOVEL Rachma, Evi Pebri Ila; Shofi Nur Aziizah
Journal of English Language Teaching, Literatures, Applied Linguistic (JELTLAL) Vol. 3 No. 2 (2025): December
Publisher : Merwinspy Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69820/jeltlal.v3i2.411

Abstract

This study aims to analyze politeness strategy used by Sherlock Holmes in Arthur Conan Doyle's novel The Sign of Four, along with the social factors that influence their use. The research uses a qualitative method, with the researcher serving as the main instrument. Data are collected by examining the dialogues involving Sherlock Holmes in the novel that contain politeness strategies. The analysis applies Brown and Levinson’s (1987) theory to identify the types of strategies used and the social factors influencing them. The analysis results show 81 data of bald on record strategies, 116 data of positive politeness strategies, 53 data of negative politeness strategies, and 7 data of off record strategies. The social factor analysis reveals 218 data of social distance and 39 data of power, while no data are found for the level of imposition.
Linguistic Branding: The Role of Word Formation in TikTok Branding Batrisya Amalia Putri; Gustary, Devian Try; Aam Alamsyah
Journal of English Language Teaching, Literatures, Applied Linguistic (JELTLAL) Vol. 3 No. 2 (2025): December
Publisher : Merwinspy Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69820/jeltlal.v3i2.435

Abstract

This study investigates the intersection of word formation and personal branding on social media, focusing on the content of a Gen Z TikTok creator named Jazzy. As TikTok serves as a dynamic platform for linguistic innovation, this research explores how a creator's language choices contribute to their digital persona. Employing a qualitative descriptive method with a morphological approach, the study analyzes five of Jazzy's most popular self-development videos. In this study, the researcher acts as the main instrument, supported by observation and note-taking techniques. The data were collected from five of Jazzy’s most-viewed TikTok videos through qualitative observation. The linguistic data were then analyzed descriptively by identifying word formation processes based on McCarthy’s (2002) theory and interpreting their relation to Rampersad’s (2008) personal branding framework. The findings reveal that compounding and derivation are the most frequently used word formation types, strategically utilized to build her brand. These linguistic choices directly support key personal branding elements, particularly specialization and authenticity. In conclusion, the study finds that linguistic creativity is not merely a reflection of online culture but a powerful, strategic tool for identity construction and audience engagement. This contributes to a broader understanding of how language and communication evolve within the context of digital media.
Effectiveness of Deep Learning–Based Reading Platforms on EFL Reading Comprehension: A Quasi-Experimental Study Anggraini, Yanti
Journal of English Language Teaching, Literatures, Applied Linguistic (JELTLAL) Vol. 3 No. 2 (2025): December
Publisher : Merwinspy Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69820/jeltlal.v3i2.441

Abstract

This study aimed to examine the effectiveness of a deep learning–based reading platform in improving EFL students’ reading comprehension achievement. A quantitative approach was employed using a quasi-experimental design, specifically the non-equivalent control group design. The sample consisted of two classes of university students (N = 60), divided into an experimental group and a control group. The experimental group used a deep learning–based reading platform equipped with adaptive reading features, difficult vocabulary analysis, AI-generated questions, and automated feedback, while the control group received conventional teaching. A 30-item reading comprehension test, validated and tested for reliability, served as the research instrument. Data were analyzed using paired sample t-tests, independent sample t-tests, and effect size calculation. The results revealed a significant improvement in the experimental group’s reading comprehension scores (p < 0.05). Furthermore, a significant difference was found between experimental and control groups in the post-test results, with an effect size of 1.30, indicating a large effect. These findings demonstrated that the deep learning–based reading platform was more effective than traditional instructional methods in enhancing EFL students’ reading comprehension.  

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