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Wanastra: Jurnal Bahasa dan Sastra
Published by Universitas Bina Sarana Informatika
ISSN : 20866151     EISSN : 25793438     DOI : https://doi.org/10.31294/wanastra
Core Subject : Education,
Languange, Linguistic, Communication & Media Other
Wanastra: Jurnal Bahasa dan Sastra appreciates and supports researchers in English studies as part of its commitment to disseminating scientific knowledge and community service. The journal provides free access to all published articles for national and international audiences. The editorial board welcomes original and innovative manuscripts in the following areas: Linguistics Literature English Language Teaching English for Specific Purposes (ESP) Submitted manuscripts must be original, properly cited, and not previously published in print or online. All submissions will be screened for plagiarism using Turnitin. Manuscripts found to contain significant plagiarism will be automatically rejected.
Arjuna Subject : Seni dan Humaniora - Bahasa dan Linguistik
Articles 34 Documents
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Decoding the 'Bad Guy': Implementing the V.O.I.C.E. Framework in Analyzing Contemporary English Song Lyrics Putra, Octa Pratama; Abdulkadir, Zubairu Sani; Anggraini, Sri Dewi
Wanastra: Jurnal Bahasa dan Sastra Vol. 18 No. 1 (2026): March
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/wanastra.v18i1.12280

Abstract

The rapid evolution of contemporary popular music has transformed songs into complex multimodal texts that often pose challenges for traditional linguistic and literary analysis. This study introduces the V.O.I.C.E framework a simplified, analytical tool to decode the multi-layered meanings of Billie Eilish’s global hit, ‘Bad Guy’. Utilizing a qualitative descriptive method grounded in Multimodal Discourse Analysis (MDA), the research examines the song through five interconnected pillars: Vocal performance, production Originality, Identity construction, Cultural circulation, and Emotional resonance. The findings reveal that ‘Bad Guy’ achieves its subversive impact by deconstructing traditional pop tropes through ASMR-like whispered vocals, minimalist ‘bedroom’ production aesthetics, and the construction of an ‘anti-hero’ persona that challenges conventional gender roles. Furthermore, the study demonstrates that the V.O.I.C.E strategy effectively bridges the gap between complex semiotic theories and practical interpretation, providing a structured yet flexible roadmap for researchers and educators. Ultimately, this research highlights a shift toward ‘New Authenticity’ in English discourse, where sonic textures and digital cultural circulation are as significant as textual content in shaping contemporary identity and global resonance.
Protagonist Agency in Epistolary Fiction: Lady Susan by Jane Austen Syarifah; Rahmah Fithriani; Pardi
Wanastra: Jurnal Bahasa dan Sastra Vol. 18 No. 1 (2026): March
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/wanastra.v18i1.12184

Abstract

Agency in literary studies is commonly approached as a moral or psychological quality of a character. However, such perspectives often overlook how agency is shaped by narrative form. This study addresses this gap by examining how the protagonist’s agency in Lady Susan is narratively constructed through epistolary mediation. This study examines the construction of the protagonist’s agency in Lady Susan, an epistolary novella in which action and intention are mediated through letters. Rather than treating agency as an ethical attribute, the study approaches agency as a product of textual mediation. Using a qualitative literary approach, the analysis employs close reading of selected letters to examine decision-making, narrative voice, and narrative consequences. This focus is significant because it clarifies how agency in epistolary fiction operates as a strategic and negotiated textual process rather than merely a reflection of character autonomy. The findings demonstrate that the protagonist’s agency is not represented as moral autonomy but as a strategic capacity negotiated through voice and social relations. Within the epistolary structure, agency emerges as a dynamic and textually constructed process.
Evaluating Naturalness in Machine Translation: A Case Study of DeepL on Philosophical Texts Hayati, Noer; Sri Wahyuni
Wanastra: Jurnal Bahasa dan Sastra Vol. 18 No. 1 (2026): March
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/wanastra.v18i1.12529

Abstract

The rapid development of Neural Machine Translation (NMT) has significantly transformed translation practices, particularly in terms of speed and accessibility. Among these systems, DeepL Translator is widely recognized for producing fluent and natural-sounding translations. However, its performance in translating complex academic discourse remains underexplored, particularly in terms of naturalness. This study aims to analyze the naturalness of Indonesian translations generated by DeepL in translating “What is a Speech Act?” by John Searle. This research employs a qualitative descriptive design. The data consist of words, phrases, clauses, and sentences selected from ten randomly sampled paragraphs of the source text and their corresponding Indonesian translations. The analysis is guided by the concept of naturalness and supported by Translation Quality Assessment frameworks. A three-point scale—natural, less natural, and unnatural—was used to evaluate the data based on semantic accuracy, lexical choice, and syntactic structure. The findings reveal that the majority of translations fall into the less natural category, indicating partial equivalence. Natural translations occur when semantic accuracy, appropriate terminology, and flexible sentence structure are achieved. In contrast, less natural and unnatural translations are characterized by literal rendering, inappropriate lexical choices, structural rigidity, and, in some cases, semantic distortion. These issues are particularly evident in segments involving abstract concepts and complex sentence structures. The study concludes that while DeepL demonstrates effectiveness in translating structurally simple and terminologically stable segments, it remains limited in handling context-dependent meaning and conceptual complexity in academic texts. Therefore, human post-editing is necessary to ensure both accuracy and naturalness. This study contributes to Translation Quality Assessment by providing empirical insights into the performance of machine translation in academic discourse and highlighting the importance of balancing semantic accuracy, lexical appropriateness, and syntactic adaptation.
AI and Multimodality-Based Authentic-Innovative Assessment for Evaluating English Speaking Skills Ibnu Subroto; Yanti Rosalinah; Cicih Nuraeni
Wanastra: Jurnal Bahasa dan Sastra Vol. 18 No. 1 (2026): March
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/wanastra.v18i1.11392

Abstract

This study aimed to develop and validate an AI-Enhanced Multimodal Authentic Assessment model for evaluating EFL students' speaking skills, addressing the limitations of conventional, subjective methods. Employing a mixed-methods approach with a qualitative-dominant design, the research involved 35 university students from a Communication and Language study program. Data were collected through authentic video-based speaking tasks, AI-assisted linguistic analysis (using Google Speech-to-Text and a ChatGPT-based evaluator), detailed multimodal rubric assessments, and student perception questionnaires. Data analysis was conducted through three procedures: multimodal performance analysis using a validated rubric, comparative analysis of AI-generated linguistic metrics, and thematic analysis of questionnaire responses. Quantitative data from AI metrics and Likert-scale questionnaire items were analyzed using descriptive statistics, while qualitative data were analyzed thematically. The findings revealed that multimodal assessment effectively captured verbal, prosodic, visual, and gestural aspects of performance. Concurrently, AI excelled at objectively analyzing micro-linguistic features such as pronunciation, speech rate, and vocabulary. The integration of human and AI evaluation created a comprehensive hybrid model that provided richer, more informative feedback. Furthermore, students expressed positive perceptions regarding the clarity and usefulness of the AI-generated feedback. The study concludes that this integrated assessment model is highly relevant for 21st-century pedagogy and enhances the accuracy and quality of oral performance evaluation. The implications suggest that educators can adopt this framework to create more objective, efficient, and holistic speaking assessments, ultimately fostering better learning outcomes.

Page 4 of 4 | Total Record : 34

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