Volume 8 | Nomor 2 | Tahun 2025 | Halaman 281Ai296
E-ISSN 2615-8655 | P-ISSN 2615-725X
http://diglosiaunmul.
com/index.
php/diglosia/article/view/1123 Comparison of the English translation of the short story Gerhana Mata using ChatGPT and Google Translate: A digital hermeneutics approach Perbandingan terjemahan cerpen AuGerhana MataAy dalam bahasa Inggris menggunakan ChatGPT dan Google Translate: Pendekatan hermeneutika digital Erika Agustiana1,*.
Nandang Hidayat2, & Widya3 Universitas Indraprasta PGRI Tanjung Barat.
Jakarta Selatan.
Indonesia Universitas Pakuan Jl.
Pakuan.
Kota Bogor.
Indonesia Email: erikaagusti4n4@gmail.
Orcid iD: https://orcid.
org/0000-0003-3910-933X Email: mr.
nandanghidayat@gmail.
Orcid iD: https://orcid.
org/0000-0002-3453-9472 Email: widya.
center@gmail.
Orcid iD: https://orcid.
org/0000-0003-4218-3928 Article History Received 10 November 2024 Revised 3 January 2025 Accepted 10 January 2025 Published 11 May 2025 Keywords translation, hermeneutic, transposition, modulation.
Kata Kunci terjemahan,hermeneutika, transposisi, modulasi, adaptasi.
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Abstract Literary translation presents a unique challenge as it involves not only transferring meaning but also preserving the style, nuances, and cultural context of the original text.
While automated translation technologies, such as Google Translate and ChatGPT, are increasingly used, questions remain about their ability to maintain meaning, aesthetics, and cultural integrity in literary texts.
This study compares the English translations of the short story Gerhana Mata produced by both tools, analyzing their strengths and weaknesses.
A digital hermeneutics approach is used to explore how meaning and cultural context are conveyed in these translations.
The research employs a qualitative, comparative design to assess the accuracy of meaning, fluency, and the ability of both tools to preserve literary style and The results highlight the importance of translation techniques such as transposition, modulation, and adaptation in maintaining grammatical accuracy and cultural relevance.
this study.
ChatGPT demonstrates superior performance compared to Google Translate in preserving the original textAos meaning and aesthetic quality.
This research contributes to the field of automatic translation, offering insights into how AI tools can be improved for literary translation and cultural preservation.
Abstrak Penerjemahan sastra menghadirkan tantangan unik karena tidak hanya memerlukan pemindahan makna, tetapi juga gaya, nuansa, dan konteks budaya dari teks asli ke dalam bahasa sasaran.
Meskipun teknologi penerjemahan otomatis seperti Google Translate dan ChatGPT semakin populer, kualitas terjemahan mereka, khususnya dalam mempertahankan makna, estetika, dan integritas budaya, masih dipertanyakan.
Penelitian ini bertujuan untuk membandingkan terjemahan bahasa Inggris cerpen Gerhana Mata yang dihasilkan oleh kedua alat tersebut, serta menganalisis kelebihan dan kekurangannya.
Pendekatan Hermeneutika digital digunakan untuk mengeksplorasi bagaimana makna dan konteks budaya diterjemahkan dalam kedua terjemahan tersebut.
Penelitian ini menggunakan pendekatan kualitatif dengan desain komparatif untuk menilai kesesuaian makna, kelancaran bahasa, serta kemampuan kedua alat dalam mempertahankan gaya dan nuansa sastra.
Hasil penelitian ini menyoroti pentingnya teknik penerjemahan seperti transposisi, modulasi, dan adaptasi dalam mempertahankan akurasi gramatikal dan relevansi budaya.
Dalam penelitian ini.
ChatGPT terbukti lebih unggul dibandingkan Google Translate dalam mempertahankan makna dan kualitas estetika teks asli.
Penelitian ini memberikan kontribusi pada bidang penerjemahan otomatis, serta memberikan wawasan tentang bagaimana alat AI dapat ditingkatkan untuk penerjemahan sastra dan pelestarian budaya.
A 2025 The Author.
Diglosia: Jurnal Kajian Bahasa.
Sastra, dan Pengajarannya by Universitas Mulawarman How to cite this article with APA style 7th ed.
Agustiana.
Hidayat.
, & Widya.
Comparison of the English translation of the short story Gerhana Mata using ChatGPT and Google Translate: A digital hermeneutics approach.
Diglosia: Jurnal Kajian Bahasa.
Sastra, dan Pengajarannya, 8.
, 281Ai296.
https://doi.
org/10.
30872/diglosia.
Diglosia: Jurnal Kajian Bahasa.
Sastra, dan Pengajarannya is an open access article under the terms of the Creative Commons Attribution-Share Alike 0 International License (CC BY-SA 4.
Erika Agustiana.
Nandang Hidayat, & Widya Introduction With the rapid advancement of AI technology, automated translation has become increasingly faster and more accessible.
Tools such as Google Translate and ChatGPT have significantly contributed to overcoming language barriers for a diverse range of users, from students to Despite these developments, translation remains indispensable for facilitating meaning transfer in communication through English and various foreign languages (Widiaswara & Jumanto, 2.
Nevertheless, the translation of literary works continues to pose considerable challenges due to the intricacies of language style, symbolic meaning, and cultural context, all of which demand a high degree of sensitivity and deep comprehension.
Literary translation is not merely a matter of conveying the literal meanings of words.
rather, it involves preserving the nuances, stylistic features, and implicit meanings embedded within the original text, necessitating specialised expertise, cultural literacy, and creative skill (Miyondri, 2.
While Google Translate is effective for everyday translation (Palupi, 2.
AI translations often tend to be literal and fail to capture the deep meaning and symbolism in literary texts.
Digital translation services are indeed fast and convenient, but their ability to maintain the aesthetics and complexity of literary texts remains questionable (Syam et al.
, 2.
According to Asnidar .
, literary translators must understand the cultural context of the original text to ensure that their translation remains authentic for the target language readers.
Translation is a complex process that involves several stages.
According to Newmark .
n Tumbole & Cholsy, 2.
, translation is a process aimed at conveying the author's intended meaning from the source language (SL) into the target language (TL) by selecting equivalent words or phrases.
Furthermore, the translator must choose the right techniques to maintain the quality and integrity of the translation (Mar et al.
, 2.
However, the choice of translation techniques can be problematic if influenced by personal preferences rather than objective standards (Risky & Firmonasari, 2.
While adaptive AI algorithms can assist with context understanding through real-time personalisation, limitations in grasping cultural sensitivity still pose significant barriers (AlAfnan, 2.
Alafnan .
also adds that while tools like Google Translate and ChatGPT offer convenience, they still struggle with the complexities of literary translation.
Literary translation requires the ability to capture symbolic meanings, cultural nuances, and linguistic depth while maintaining the style and beauty of the original text.
As Newmark .
points out.
Cultural limitations mostly arise from the unique lifestyles and their expressions within communities that utilize language as a means of communication (Lestari & Sutrisno, 2.
Therefore, literary translation requires precision, creativity, and cultural sensitivity to produce high-quality and authentic translations.
Based on these opinions, it can be concluded that while AI translation tools like Google Translate and ChatGPT are fast and convenient, they still face difficulties in translating complex literary works.
Literary translation is not just about transferring words.
it also involves preserving deep cultural nuances, style, and meaning.
This requires expertise and cultural understanding that cannot be fully replaced by AI technology.
Therefore, human translators are still needed to ensure that the translation remains authentic and of high quality.
This study analyzes the short story Gerhana Mata by Djenar Maesa Ayu, selected for its unique symbolism and language style (Ayu, 2.
These characteristics pose significant challenges for AI translation, which often struggles with capturing philosophical and cultural nuances.
Hermeneutics, as discussed by Isensee (Rakhmaniar, 2.
, plays a crucial role in interpreting meaning in written texts.
According to Schleiermacher, hermeneutics is the science of understanding texts through a systematic method (Al Munir, 2.
Its goal is to uncover implied meanings, which is vital in literary translation (Mahatma, 2.
Identifying an equivalent in the target language that faithfully conveys the source textAos message is essential (Lubis, 2.
However.
AI tools like Google Translate still encounter difficulties in accurately translating cultural contexts (Jumatulaini, 2.
Diglosia: Jurnal Kajian Bahasa.
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281Ai296 Comparison of the English translation of the short story Gerhana Mata using ChatGPT and Google Translate: A digital hermeneutics approach This study employs a digital hermeneutics approach to analyze how ChatGPT and Google Translate understand and convey the meaning of the short story Gerhana Mata, both explicitly and implicitly, through techniques like transposition, modulation, and adaptation.
Transposition looks at changes in language structure to maintain clarity in the target language, as outlined by Vinay and Darbelnet, transformations in grammatical forms between the source and target languages (Rahmah, 2.
This technique can be either required or optional, depending on the need for clarity (Naserly, 2.
Modulation assesses AIAos ability to adjust perspectives while preserving nuances and the intended message, ensuring it resonates with the target audience (Mardiana, 2.
Adaptation addresses cultural elements without direct equivalents in the target language, ensuring that the translation aligns with the audienceAos cultural context and expectations (Siregar, 2.
This study explores the ability of ChatGPT and Google Translate to translate complex literary texts, such as Gerhana Mata, by applying digital hermeneutics to assess their sensitivity to symbolic and cultural elements.
The analysis of transposition, modulation, and adaptation evaluates how well AI tools preserve the meaning and aesthetics of the text.
Advances in AI, particularly through deep learning techniques, enhance accuracy and contextual understanding in translations, breaking down language barriers and fostering cross-cultural communication (Mohamed et al.
, 2.
This research contributes to the literature on digital translation, highlighting the strengths and limitations of AI as a translation tool, and helps educators and students understand the role of AI and digital hermeneutics in translating literary texts.
This study aims to assess the abilities of ChatGPT and Google Translate in translating literary texts, specifically Gerhana Mata, through a digital hermeneutic approach.
By examining techniques such as transposition, modulation, and adaptation, the research investigates how effectively these tools convey symbolic and cultural meanings.
The findings compare the cultural accuracy and relevance of translations from both platforms, highlighting their strengths and limitations in literary The study seeks to improve the understanding of AI's role in literary translation and offer recommendations for developing AI-based translation technologies that better address cultural context and hermeneutic elements for academic and practical purposes.
Rahmah .
defines translation as a process of communication that conveys messages from the source language (SL) to the target language (TL), addressing both linguistic and cultural This process ensures the translated text meets the audience's needs while maintaining the original meaning and information.
Mar .
highlights the importance of understanding the lexicon, grammar, and context of the source language, while Asnidar .
stresses the role of cultural context in ensuring translation appropriateness.
Naserly .
emphasizes translation as a cross-linguistic and cross-cultural process, requiring the preservation of meaning accuracy alongside cultural respect.
Hermeneutics, the study of interpretation, is essential in literary translation as it uncovers deeper meanings.
Derived from the Greek word hermeneuein .
o interpre.
, hermeneutics emphasizes understanding texts within cultural and social contexts (Suwardi & Syaifullah, 2.
Initially applied to classical and sacred texts, hermeneutics has also influenced various other fields (Al Munir, 2.
Paul Ricoeur's hermeneutic framework explores the relationship between the author, text, and reader, helping to uncover both literal and implied meanings (Iman, et al, 2.
Hermeneutics is a theory of interpretation that provides a foundation for understanding the literature review process, where understanding is not just cognitive but also part of human existence, universal to all human activity (Boell & Cecez-Kecmanovic, 2.
Building on these theoretical foundations, this study evaluates the translation performance of ChatGPT and Google Translate on Gerhana Mata.
Using a digital hermeneutic approach, it examines how these tools capture symbolic and cultural nuances through techniques like transposition, modulation, and adaptation.
These methods address grammatical restructuring, perspective shifts, and cultural adjustments when translating to the target language.
AIAos role in translation is expanding, offering potential advancements in education and other In Indonesia, tools like Google Translate and ChatGPT reduce dependence on traditional resources and facilitate learning (Nabila, 2.
While Google Translate excels in providing quick.
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281Ai296 Erika Agustiana.
Nandang Hidayat, & Widya practical translations (Palupi, 2.
ChatGPT offers more sophisticated interactions, fostering deeper linguistic and educational applications (Suharmawan, 2.
This study contributes to the ongoing discourse on AI-assisted literary translation by comparing the strengths and weaknesses of these tools and exploring how digital hermeneutics can improve the interpretation of literature.
Method Hermeneutics emphasized interpreting texts to uncover deeper meanings, acknowledging that interpretation is a continuous process (Boell & Cecez-Kecmanovic, 2.
It functioned through two interconnected cycles: one focused on analysis and interpretation, and the other on exploration and acquisition, which collectively enhanced understanding.
The hermeneutic approach was selected to explore the text's deeper meanings by analyzing its context, the authorAos intent, and the readerAos interpretation.
It facilitated the identification of semantic nuances in translations and examined the impact of translation tools like Google Translate and ChatGPT on changes in The literature review process also adhered to a hermeneutic framework, where initial ideas initiated a cycle of searching, sorting, and acquiring sources, while reading refined the search Analytical activities such as mapping, classification, and critical assessment built upon this search cycle to deepen understanding.
A flowchart was created to visualize the steps involved in translating a short story using a digital hermeneutic approach, with arrows illustrating the process flow between each step.
Text Story of Gerhana Mata Initial Translation Hermeneutic Analysis Translation Process:
Transposition Modulation Adaptation Documents Reflexional Revision and Refinement Critical Evaluation Figure 1.
The Translation Process The translation of a short story from Indonesian to English using a digital hermeneutic approach encompassed multiple stages.
Initially, the short story was digitized, followed by generating an initial translation draft with Google Translate.
Subsequently, a more contextual and nuanced translation was created using ChatGPT.
The outputs from both tools were then analyzed, focusing on refining aspects such as structure, perspective, and cultural nuances through techniques like transposition, modulation, and adaptation.
Revisions were made to enhance linguistic fluency and ensure fidelity to the original text, culminating in a critical evaluation and documentation of the differences between the two translations.
This process contributed to the exploration of digital hermeneutics in translation studies.
The study utilized data derived from translating Gerhana Mata into English using both ChatGPT and Google Translate.
These translations were analyzed within a digital hermeneutic framework, inspired by the iterative process outlined by Boell and Cecez-Kecmanovic .
This methodology emphasized repeated cycles of analysis and interpretation to uncover explicit and implicit meanings within the text.
Three primary analytical techniques were employed: first, transposition.
This technique is the replacement of a grammatical unit with another of a different word class, maintaining the same meaning, guided by Vinay and DarbelnetAos principles (Saridaki, 2.
For instance, the source text (ST) sentence AuCahaya rembulan menari di atas daun kelapaAy was translated by Google Translate (GT) as AuThe moonlight dances on the coconut leavesAy and by ChatGPT (GPT) as AuMoonlight shimmering Diglosia: Jurnal Kajian Bahasa.
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281Ai296 Comparison of the English translation of the short story Gerhana Mata using ChatGPT and Google Translate: A digital hermeneutics approach across the palm leaves.
Ay While both maintain the original meaning.
GPTAos choice of AushimmeringAy added a poetic nuance not explicitly present in the source text.
Second, modulation.
Modulation is a change in perspective that adjusts the form of the message, used when a translation is grammatically correct but inappropriate in the target language (Saridaki, 2.
For example, the ST sentence AuMatahari menghilang di balik awan kelabuAy was rendered by GT as AuThe sun disappears behind gray cloudsAy and by GPT as AuThe sun hides behind gray Ay The shift from AudisappearsAy to AuhidesAy reflects a perspective adjustment, creating a stronger emotional impact while retaining the original essence.
Third, adaptation.
Adaptation involves changing cultural references in the source text to fit the socio-cultural context of the target language, creating an equivalent situation (Saridaki, 2.
For instance, the ST phrase AuMenari di bawah rindang beringin, seperti tokoh dalam cerita rakyatAy was translated by GT as AuDancing under the shady banyan tree, like characters in folk talesAy and by GPT as AuDancing beneath the banyan tree, reminiscent of folklore heroes.
Ay While GT provided a literal translation.
GPT adapted the phrase to better align with English cultural norms, albeit with a slight shift in meaning.
The systematic use of these techniques highlighted how semantic and stylistic nuances were either preserved or adjusted.
A flowchart visually outlined the translation process, depicting the iterative steps from text preparation to critical evaluation.
Results and Discussion The Data and Discussion section presents the results of the analysis of the Indonesian-toEnglish text translation, conducted using a digital hermeneutic approach.
This approach focuses on the application of translation techniques outlined in Vinay and DarbelnetAos framework, as referenced by Saridaki .
Specifically, the study examines the use of transposition, modulation, and adaptation, which belong to the category of oblique translation techniques.
Through the digital hermeneutic approach, this study aims to assess how these techniques preserve the integrity of meaning, nuance, and cultural context of the source text.
Additionally, this approach examines the strengths and limitations of automatic translation tools in handling texts with high symbolic and aesthetic value, such as the short story Gerhana Mata.
To facilitate the analysis, the researcher employs abbreviation codes to identify the source of quotations.
The code ST (Source Tek.
refers to direct quotes from the short story in its original Indonesian version.
GT (Google Translat.
, and GPT (ChatGPT).
The paragraph numbers indicate the specific location in the Gerhana Mata text from which the quotations are taken.
By analyzing how these techniques influence the translation process and outcomes, this study provides insights into the fidelity and adaptability of machine-generated translations, particularly when applied to literary texts that demand a nuanced understanding of cultural and aesthetic elements.
Paragraph 1 Transposition ST : AuMalam selalu memberi ketenangan.
Ay GT : AuNight always brings peace.
Ay GPT : AuThe night always brings peace.
Ay The GT Translation and GPT Translation show transposition in the change of the phrase AumalamAy to Authe night.
Ay The GPT Translation uses Authe nightAy to add a definite nuance, as if referring to a specific night that holds personal meaning for the narrator.
Digital hermeneutics here suggests that this choice may add depth to the contextual meaning, making the night more emotionally significant in the context of the narrative.
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Nandang Hidayat, & Widya Modulation TS : AuBanyak kenangan yang begitu mudah dikais dalam ruang-ruang kegelapan.
Ay GT : AuMany memories are so easy to find in dark spaces.
Ay GPT : AuSo many memories are easy to gather in the darkness.
Ay In the GT Translation, the word AudikaisAy is translated as Aufind,Ay whereas in the GPT Translation, it is changed to Augather.
Ay From a hermeneutic perspective, the choice of AugatherAy is more appropriate for this literary context because it evokes an emotional image that is closer to the original atmosphere.
AuFindAy tends to mean AudiscoverAy without effort, while AugatherAy carries the connotation of intentionally collecting memories, as if there is a need or longing to gather them.
The modulation in the GPT Translation shows a more emotionally nuanced interpretation that aligns better with the contemplative tone of the original text.
Adaptation ST : Audi atas pembaringan tanpa kekasih yang tak akan hadir.
Ay GT : Auin bed without a lover who will not be present.
Ay GPT : Auover a bed without a lover who will never come.
Ay In this phrase, the GPT Translation uses the expression Auwho will never comeAy instead of Auwho will not be presentAy in the GT Translation.
From a hermeneutic approach, the adaptation in the GPT Translation adds a stronger emotional depth and sense of despair.
The choice of Auwho will never comeAy creates a more poignant atmosphere of loneliness, in line with the sadness portrayed in the original text.
From a digital hermeneutic perspective, the GPT Translation successfully captures a deeper nuance and contextual meaning compared to the GT Translation.
The hermeneutic approach here helps assess how automatic translation tools can approach the rich literary meaning filled with emotion, and how each translation technique plays a role in creating or preserving the depth of meaning in the target language.
Therefore, overall, the GPT Translation shows a deeper understanding of the emotional and cultural context of the original text.
Paragraph 2 Transposition ST : AuBanyak orang yang begitu takut pada malam.
Pada gelapAy.
AuMembuat jantung mereka berdegup lebih kencangAy GT : AuIn the darkAy AuMakes their hearts beat fasterAy GPT : AuOf darknessAy AuIt makes their hearts race fasterAy In terms of AutranspositionAy the GT and GPT translations show differences in phrase selection.
For example, in the GT translation.
AuPada gelapAy is translated as AuIn the darkAy which sounds less natural in English.
Meanwhile.
GPT adapts more appropriately with Auof darknessAy which better fits the English structure.
The phrase AuMembuat jantung mereka berdegup lebih kencangAy is transpositionally translated as AuMakes their hearts beat fasterAy in GT and AuIt makes their hearts race fasterAy in GPT.
The GPT translation is more accurate because it uses a more common sentence structure in English, while GT maintains the original structure.
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281Ai296 Comparison of the English translation of the short story Gerhana Mata using ChatGPT and Google Translate: A digital hermeneutics approach Modulation ST : Aumata kita seolah butaAy GT : Aumakes our eyes feel blindAy GPT : AuOf something that makes our eyes feel blind, forcing us to grope aroundAy The GPT translation demonstrates modulation in the sentence AuOf something that makes our eyes feel blind, forcing us to grope aroundAy where this phrase not only changes the words but also conveys the subjective sensation of Aumata kita seolah butaAy .
ur eyes feeling as though they are blin.
Meanwhile, the GT translation becomes Aumakes our eyes feel blind.
Ay The GPT translation adds an emotional nuance, making it feel more natural and reflective in English.
In contrast, the GT translation uses minimal modulation, with words that tend to be more literal, making it sound less smooth and somewhat more rigid.
Adaptation ST : Auharga listrik,Ay GT : Aueven as its cost keeps soaring,Ay GPT : Augetting higher and higherAy Both translations show adaptation in the final phrase regarding Auharga listrikAy .
lectricity price.
, but GPT is slightly more effective.
The GPT translation uses Aueven as its cost keeps soaringAy which dramatically depicts the rising price using the common English term Aukeeps soaring.
Ay This resonates more strongly in English than Augetting higher and higherAy in the GT translation, which tends to be less expressive.
The digital hermeneutics approach emphasizes the interpretation of meaning based on the nuances of words within the cultural context.
The GPT translation excels in terms of transposition, modulation, and adaptation, using words and structures that are not only grammatically correct but also convey a deeper meaning consistent with the original Indonesian interpretation.
Paragraph 3 Transposition ST : Ausemakin ramaiAy AuTubuh kelihatan amat samar.
Ay GT : AuThe darker it gets, the busier it getsAy AuThe body looks very vague.
Ay GPT : AuBodies appear so faint,Ay AuThe livelier it becomes,Ay In the GT translation, the sentence structure is fairly close to the original language, but in some parts, it sounds stiff in English.
For example.
AuThe body looks very vagueAy feels unnatural, while GPT rephrases the sentence as AuBodies appear so faintAy which is more natural and easier to read.
In the phrase AuThe darker it gets, the busier it getsAy in GT, the use of AubusierAy is less accurate, while GPT opts for the phrase Authe livelier it becomesAy which better captures the atmosphere and the sense of Ausemakin ramaiAy (Auincreasingly livelyA.
intended in the original text.
Modulation ST : Auhampir menyerupai pasar malam yang ingar bingar namun tanpa penerangan,Ay Ausemakin semuanya akhirnya begitu terang terlihat.
Ay GT : Aunoisy night market but without lighting,Ay Authe darker it got, the more everything finally became so brightly visibleAy Diglosia: Jurnal Kajian Bahasa.
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Nandang Hidayat, & Widya GPT : Aubustling night market, but without any lights.
Ay Authe darker it gets, the clearer everything becomes,Ay In the phrase Auhampir menyerupai pasar malam yang ingar bingar namun tanpa peneranganAy GT uses Aunoisy night market but without lightingAy while GPT translates it as Aubustling night market, but without any lightsAy Here.
GPT modulates Auingar bingarAy to AubustlingAy which conveys a lively crowd, aligning with the nighttime atmosphere depicted in the original text.
Modulation is also evident in the last phrase.
In GT, the phrase Authe darker it got, the more everything finally became so brightly visibleAy uses words that are somewhat literal and could feel GPT presents it as Authe darker it gets, the clearer everything becomesAy which better captures the essence of the visual paradox more clearly and directly.
Adaptation ST : Auada perasaan kedekatan suara dan napas yang sangat intens, hampir seolah-olah terasa dekat Ay AuSemakin gelap semakin ramai.
Hampir menyerupai pasar malam yang ingar bingar namun tanpa penerangan.
Ay GT : Auso near that I can even smell the breath of the voice's owner lingering near my nose,Ay AuThe darker it gets, the busier it gets.
Almost like a noisy night market but without lighting.
Ay GPT : Ausmell of the voice's owner's breath lingered in my nose,Ay AuThe darker it gets, the livelier it becomes.
Almost like a bustling night market, but without any Ay In the original text.
Auada perasaan kedekatan suara dan napas yang sangat intens, hampir seolah-olah terasa dekat sekaliAy GPT successfully captures this with the sentence Auso near that I can even smell the breath of the voice's owner lingering near my noseAy which gives a more intimate and realistic nuance.
GT uses Ausmell of the voice's owner's breath lingered in my noseAy which sounds less refined and somewhat odd in English.
Overall, the adaptation in GPT feels more attuned to the emotional and visual context of the original text.
Choices like AulivelierAy and Aubustling night marketAy make GPT more cohesive and stronger in capturing the cultural context of the source language compared to the choices of AubusierAy and Aunoisy night market.
Ay In the digital hermeneutics approach.
GPT effectively conveys the nuances of the original The more natural sentence structure and more appropriate word choices in GPT offer an experience that closely mirrors the intensity and contradictory calmness felt by the author in the original text.
Paragraph 4 Transposition ST : AuSaya tidak butuh kacamata matahari demi mendapatkan gelap di kala siang menyala.
Ay AuSaya hanya perlu mencinta dan dengan seketika butalah mata saya.
Ay GT : AuI don't need sun glasses to get dark when it's daylightAy AuI just need to love and instantly my eyes are blind.
Ay GPT : AuI donAot need sunglasses to find darkness when daylight blazes,Ay AuI only need to love, and instantly my eyes are blind.
Ay The GT translation largely follows the sentence structure of Indonesian directly, but this makes it somewhat stiff in English.
For example.
AuI don't need sun glasses to get dark when it's daylightAy sounds Diglosia: Jurnal Kajian Bahasa.
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281Ai296 Comparison of the English translation of the short story Gerhana Mata using ChatGPT and Google Translate: A digital hermeneutics approach Meanwhile, the GPT translation adjusts the sentence to AuI donAot need sunglasses to find darkness when daylight blazes,Ay which sounds more natural and poetic.
At the end of the paragraph, the GPT translation uses a more poetic structure in the sentence AuI only need to love, and instantly my eyes are blind,Ay which sounds smoother than the GT version.
AuI just need to love and instantly my eyes are blind.
Ay Modulation ST : AuSeperti malam.
Seperti gelap.
Ay Audemi mendapatkan gelap di kala siang menyala.
Ay GT : AuLike night.
Like dark.
Ay Auto get dark when it's daylight.
Ay GPT : AuLike the night.
Like darkness.
Ay Auto find darkness when daylight blazes.
Ay The GT translation uses AuLike night.
Like dark,Ay which comes across as more literal and may feel less poetic compared to AuLike the night.
Like darknessAy in the GPT translation.
The modulation in GPT makes the word choice more expressive and emphasizes the beauty of the language desired in the original text.
In the phrase Audemi mendapatkan gelap di kala siang menyala,Ay GT uses Auto get dark when it's daylight,Ay which is more literal.
The GPT translation modulates it to Auto find darkness when daylight blazes,Ay adding an aspect of intensity to Ausiang menyala,Ay making it more in line with the tone of the original text.
Adaptation ST : Aumungkin karena itulah saya begitu membutuhkan cintaAy AuCinta pun membutakanAy GT : AuMaybe that's why I need love so muchAy AuLove is blindingAy GPT : AuPerhaps thatAos why I crave love so deeply.
Ay AuLove, too, blinds.
Ay Phrases like Aumungkin karena itulah saya begitu membutuhkan cintaAy are better adapted in the GPT translation as AuPerhaps thatAos why I crave love so deeply.
Ay The word AucraveAy conveys a sense of longing or deep need, which aligns more strongly with the emotional context intended in the Indonesian text.
In the original text, there is a metaphor about love AublindingAy like the darkness of night.
The GPT translation uses a subtle adaptation with AuLove, too, blinds,Ay compared to the GT translation, which uses AuLove is blinding.
Ay The word choice in GPT conveys the effect of love's darkness in a more poetic manner, in keeping with the contemplative mood.
The digital hermeneutic approach examines the text based on emotional context and deeper meaning, not just words.
The GPT translation succeeds in capturing and conveying the poetic and reflective nuances of the original text more effectively.
It shows a closer alignment with English stylistic conventions, capturing the philosophical essence and emotions embedded in the original, producing a more aesthetic and harmonious translation in meaning.
Paragraph 5 Transposition ST : AuSaya menamakan kebutaan itu gerhana mata.
Ay AuDan hanya ialah yang saya ingin lihat, sang kekasih bak lentera benderang dalam kegulitaan pandangan mata saya.
Ay GT : AuI call blindness the eclipse of the eye.
Ay Diglosia: Jurnal Kajian Bahasa.
Sastra, dan Pengajarannya Vol.
8 No.
281Ai296 Erika Agustiana.
Nandang Hidayat, & Widya AuAnd thatAos the only thing I want to see, my lover like a bright lantern.
Ay GPT : AuI call this blindness an eclipse of sight.
Ay AuAnd he alone is what I wish to seeAithe beloved, like a bright lanternAAy The GT translation tends to retain the direct structure of the original language, as seen in AuI call blindness the eclipse of the eye,Ay which sounds less natural in English.
The GPT translation uses AuI call this blindness an eclipse of sight,Ay which is more expressive and fluid, with AusightAy replacing AueyeAy to enhance the symbolic meaning.
In the line AuAnd thatAos the only thing I want to see, my lover like a bright lantern,Ay the GT translation keeps the original structure but is less poetic compared to GPT, which rephrases it as AuAnd he alone is what I wish to seeAithe beloved, like a bright lanternAAy The GPT structure flows more smoothly and demonstrates a transposition that makes it more poetic.
Modulation ST : AuApa pun namanya saya tidak peduli.
Ay AuDari sinarnyalah saya mendapatkan siang yang kami habiskan di ranjang-ranjang pondok Ay GT : AuWhatever itAos called I donAot care.
Ay AuIt was from its light that I got the afternoon we spent in the beds of the inn.
Ay GPT : AuWhatever the name.
I donAot care.
Ay AuFrom his light.
I find the day we spend in the beds of small inns.
Ay In the phrase AuApa pun namanya saya tidak peduli,Ay the modulation in the GPT translation uses AuWhatever the name.
I donAot care,Ay which sounds more formal and impactful compared to GTAos AuWhatever itAos called I donAot care.
Ay This small difference enhances the expression's depth without losing meaning.
In the phrase AuDari sinarnyalah saya mendapatkan siang yang kami habiskan di ranjang-ranjang pondok penginapan,Ay GT translates it as AuIt was from its light that I got the afternoon we spent in the beds of the inn.
Ay Meanwhile.
GPT, with a subtle modulation, renders it as AuFrom his light.
I find the day we spend in the beds of small inns,Ay which conveys a more fitting sense of intimacy and contemplation true to the original textAos tone.
GPTAos modulation uses AufindAy and Ausmall innsAy to add an emotional Adaptation ST : Ausang kekasih bak lentera benderang dalam kegulitaan pandangan mata saya.
Ay AuDan melenguh seakan hanya siang itu hari terakhir kami bisa saling mengeluarkan lenguhan.
Ay GT : Aumy lover like a bright lantern in the darkness of my eyes.
Ay AuAnd moaned as if that afternoon was the last day we could moan to each other.
Ay GPT : Authe beloved, like a bright lantern in the depths of my visionAos darkness.
Ay AuAnd sighing as if that day were the last weAod ever let out those sighs together.
Ay In the GPT translation, the phrase Authe beloved, like a bright lantern in the depths of my visionAos darknessAy provides a stronger emotional adaptation compared to GTAos Aumy lover like a bright lantern in the darkness of my eyes.
Ay GPT offers more symbolic and delicate word choices to convey the speaker's feelings toward their lover.
Adaptation is also evident in the final sentence: GPT uses Ausighing as if that day were the last weAod ever let out those sighs together,Ay which better captures the depth of AumelenguhAy as an intimate In GT, the use of AumoanedAy sounds more literal and less emotionally fitting.
Diglosia: Jurnal Kajian Bahasa.
Sastra, dan Pengajarannya Vol.
8 No.
281Ai296 Comparison of the English translation of the short story Gerhana Mata using ChatGPT and Google Translate: A digital hermeneutics approach The digital hermeneutic approach involves a profound understanding of the cultural context and emotional meaning of the original text.
Translation GPT performs better in conveying the original textAos meaning and nuances due to its more flexible transposition, modulation that enhances emotional expression, and adaptation that captures the sense of intimacy and underlying sadness in the text.
GPT demonstrates a higher sensitivity to metaphors and reflective atmosphere, making it feel more harmonious and poetic in English.
Paragraph 6 Transposition ST : Ausaya tak perlu meraba-raba.
Ay AuSemakin kabur.
Semakin dalam ke muara cinta tubuh ini terceburAy GT : AuI donAot need to fumble.
Ay AuItAos getting blurry.
Deeper into the estuary of love this body plunges.
Ay GPT : AuI donAot need to grope my way around.
Ay Aublurring further, sinking deeper into the river of love into which my being has fallen.
Ay The GT translation adheres more closely to the direct structure of the original language, as seen in AuI donAot need to fumble,Ay which feels slightly awkward in English.
In GPTAos translation, this is adapted to AuI donAot need to grope my way around,Ay which is clearer and sounds more natural in the context of describing blindness.
The phrase AuSemakin kabur.
Semakin dalam ke muara cinta tubuh ini terceburAy is translated directly by GT as AuItAos getting blurry.
Deeper into the estuary of love this body plunges.
Ay Meanwhile.
GPT uses Aublurring further, sinking deeper into the river of love into which my being has fallen.
Ay The structure in GPT flows more naturally and adds a poetic nuance.
Modulation ST : AuTidak ada apa pun di dunia ini yang lebih penting dari saya.
Ay Augerhana mata bekerja.
Ay GT : AuThere is nothing in this world that is more important than me.
Ay Authe eclipse of the eye immediately works.
Ay GPT : AuNothing else in this world is more important than me.
Ay Aumy eclipse of sight takes over immediately.
Ay In the phrase AuTidak ada apa pun di dunia ini yang lebih penting dari saya,Ay GT translates it as AuThere is nothing in this world that is more important than me,Ay which sounds slightly formal.
GPTAos translation.
AuNothing else in this world is more important than me,Ay feels more expressive and natural.
In the phrase Augerhana mata bekerja,Ay GT translates it as Authe eclipse of the eye immediately works,Ay which sounds somewhat literal.
GPTAos translation.
Aumy eclipse of sight takes over immediately,Ay provides a smoother and more dramatic effect.
Adaptation ST : AuSaya tetap mendengar suaranya melantunkan senandung yang membuat saya merasa itulah saat terindah untuk sekarat.
Ay Auke muara cinta tubuh ini tercebur.
Ay GT : Auhumming a song that made me feel like it was the most beautiful moment to die.
Ay Auestuary of loveAy GPT : Auhumming a tune that makes me feel as though itAos the most beautiful moment to surrender.
Ay Auinto the river of love into which my being has fallen.
Ay Diglosia: Jurnal Kajian Bahasa.
Sastra, dan Pengajarannya Vol.
8 No.
281Ai296 Erika Agustiana.
Nandang Hidayat, & Widya In the phrase AuSaya tetap mendengar suaranya melantunkan senandung yang membuat saya merasa itulah saat terindah untuk sekarat,Ay GT translates it as Auhumming a song that made me feel like it was the most beautiful moment to die.
Ay The use of Auto dieAy feels literal, whereas GPT adapts this to Auhumming a tune that makes me feel as though itAos the most beautiful moment to surrender,Ay which is deeper and captures the emotional intent more effectively.
In the final part.
Auke muara cinta tubuh ini terceburAy is translated by GPT as Auinto the river of love into which my being has fallen,Ay compared to GTAos Auestuary of love.
Ay GPTAos translation is more adaptive, adding a poetic touch with Auriver of loveAy and Aumy being,Ay creating a deeper sense of romance and vulnerability.
With a digital hermeneutic approach that includes contextual and emotional understanding.
GPTAos translation successfully conveys a deeper, more reflective nuance of the original text.
The transposition and modulation in GPT produce smoother and more poetic sentences, while adaptation enriches the implied emotions.
GPTAos translation is more aligned with the original text's philosophical and emotional tones, emphasizing the intoxicating blindness of love and flowing in English with a more vibrant and symbolic expression.
Paragraph 7 Transposition ST : AuKala api rindu sudah semalaman memanggang.
Ay AuSegala garis maupun lekukan amat nyata terlihat dengan mata telanjang.
Ay GT : AuWhen the fire misses it has been roasting all night.
Ay AuWhen all the lines and curves are very clearly visible to the naked eye.
Ay GPT : Auwhen the fire of longing has smoldered through the night.
Ay Auwhen every line and curve is vividly seen with the naked eye.
Ay In GTAos translation.
AuWhen the fire misses it has been roasting all night,Ay the sentence sounds somewhat awkward and unnatural.
GPTAos translation is more precise, using Auwhen the fire of longing has smoldered through the night,Ay which is not only smoother but also more poetic.
GPT rearranges sentence elements to enhance flow and elevate the beauty of the language.
The phrase AuSegala garis maupun lekukan amat nyata terlihat dengan mata telanjangAy is directly translated by GT as AuWhen all the lines and curves are very clearly visible to the naked eye,Ay but GPT chooses Auwhen every line and curve is vividly seen with the naked eye,Ay which feels more vibrant and visually evocative.
Modulation ST : AuKala api rindu sudah semalaman memanggang.
Ay AuDi sanalah kami saling menjamu keinginan.
Ay GT : AuWhen the fire misses it has been roasting all night.
Ay AuThat's where we entertain each other's wishes.
Ay GPT : Auwhen the fire of longing has smoldered through the night.
Ay AuIt is there that we serve each other's desires.
Ay In the sentence AuKala api rindu sudah semalaman memanggang,Ay GT uses the literal phrase AuWhen the fire misses it has been roasting all night.
Ay This fails to capture the emotional nuance of longing in the original language.
GPTAos modulation.
Auwhen the fire of longing has smoldered through the night,Ay is more accurate as it conveys the slow, intense burn of longing.
For the phrase AuDi sanalah kami saling menjamu keinginan,Ay GT chooses AuThat's where we entertain each other's wishes,Ay which feels somewhat flat and literal.
GPTAos translation.
AuIt is there that we serve each other's desires,Ay modulates Auserve,Ay imparting a deeper, more intimate meaning.
Diglosia: Jurnal Kajian Bahasa.
Sastra, dan Pengajarannya Vol.
8 No.
281Ai296 Comparison of the English translation of the short story Gerhana Mata using ChatGPT and Google Translate: A digital hermeneutics approach Adaptation ST : AuSegala garis maupun lekukan itu selalu diikuti bayang-bayang.
Ay AuDan dalam bayang-bayang itulah kami betemu dan bersatu GT : AuAll lines and curves are always followed by shadows.
Ay AuAnd it is within those shadows that we meet and become one.
Ay GPT : AuEvery line and curve is always followed by shadows.
Ay AuAnd it was in the shadows that we met and united.
Ay In the phrase AuSegala garis maupun lekukan itu selalu diikuti bayang-bayang,Ay GT retains the literal structure.
AuAll lines and curves are always followed by shadows,Ay which feels slightly stiff.
GPTAos version is more expressive with AuEvery line and curve is always followed by shadows,Ay offering a softer, more poetic feel that captures the idea of shadows accompanying each shape and curve in an intimate The final sentence AuDan dalam bayang-bayang itulah kami betemu dan bersatuAy is translated by GPT as AuAnd it is within those shadows that we meet and become one.
Ay The phrase Aubecome oneAy replaces AuunitedAy in GT, providing a stronger romantic and poetic nuance that aligns with the emotional context of the original text.
Using a digital hermeneutic approach.
GPT captures a stronger emotional and symbolic context than GT.
GPT not only rearranges words for a more natural transposition but also modulates terms like AusmolderedAy and AuserveAy to enrich the profound feelings and longing within the The adaptation in GPTAos translation creates a more intimate and poetic reading experience, staying closer to the philosophical and romantic tones present in the original text.
Conclusion The application of a digital hermeneutic approach through the analysis of transposition, modulation, and adaptation in translation yields remarkable results.
In the aspect of transposition.
GPT demonstrates its strength in replacing words or phrases to create a deeper readability and emotional resonance.
For instance, the choice of Authe nightAy to replace AumalamAy not only conveys the meaning but also provides a more profound emotional impact, drawing the reader closer to the essence of the intended feeling.
In modulation.
GPT can reframe words in a way that is more expressive and natural, creating richer, deeper meanings.
For example, the phrase Aucrave loveAy conveys a deeper emotional need compared to Auneed love,Ay which sounds flatter.
Additionally, by adding a dramatic touch to the statement about electricity prices.
GPT successfully clarifies the connotation of price hikes in a more vivid and striking way than the simpler literal translation.
The adaptation in GPTAos translation reflects the emotional and cultural richness of the target For example, the expression Authe beloved, like a bright lanternAy provides a much more intimate and emotional image, far surpassing the literal translation, which feels flat.
GPT also succeeds in incorporating poetic elements that enrich the depiction of the relationship between the subject and their lover, making it feel more alive and meaningful.
Overall.
GPT proves to be more effective in producing translations that not only retain meaning but also bring out the context and emotional nuances.
Compared to more literal machine translations.
GPT shows its ability to create texts that are deeper, more natural, and emotionally resonant, aligning more closely with the original intent of the text.
References