Metode Penerjemahan Metafora pada Novel Peter Pan Karya J.M. Barrie
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Tujuan penelitian ini adalah untuk mengungkapkan dan mendeskripsikan metode-metode penerjemahan metafora dalam novel Peter Pan karya J.M. Barrie. Hal itu disebabkan oleh metafora merupakan bahasa figuratif yang dalam proses penerjemahannya ditemukan kesulitan untuk mencari kesepadanannya dalam bahasa sasaran. Dalam penelitian ini, proses penerjemahan tersebut dianalisis melalui delapan metode penerjemahan, yakni penerjemahan kata per kata, penerjemahan literal, penerjemahan setia, penerjemahan semantis, penerjemahan komunikatif, penerjemahan idiomatis, penerjemahan bebas, dan penerjemahan adaptasi. Sementara itu, penelitian ini merupakan penelitian deskriptif komparatif, yaitu membandingkan metafora dalam novel Inggris dalam novel Peter Pan dengan terjemahan metafora dalam novel terjemahan berbahasa Indonesia. Data metafora dianalisis secara kualitatif berdasarkan metode penerjemahannya. Hasil analisis menunjukkan bahwa (1) perbedaan sistem kebahasaan serta pola pikir pengguna bahasa sumber dengan bahasa sasaran menyebabkan tidak semua metafora dapat diterjemahkan dengan menggunakan padanan metafora dalam bahasa sasaran dan (2) dengan menggunakan metafora yang tepat, penerjemah dapat menyampaikan berbagai makna metafora teks sumber ke dalam teks sasaran tanpa mengubah makna dan citranya.Metaphor is a figurative language whose formation is influenced by cultural background thus the equivalent of source language cannot necessarily be found in the target language. The application of the translation methods can affect the result of translation equivalent. Therefore, this research aims to identify and describe the methods of metaphor translation in the J.M. Barrie’s novel, “Peter Pan”. This is a comparative research since it compares the metaphors found in the English source novel with their translations in its Indonesian translated novel. The metaphorical expressions used as the data are in the form of word, phrase, and clause which were taken purposively and were analyzed descriptively qualitatively based on Newmark’s theory of translation methods. The result shows that (1) there are eight translation methods which are used by the translator such as word-for-word translation, literal translation, faithful translation, semantic translation, communicative translation, idiomatic translation, free translation, and adaptation translation; (2) the difference in the linguistic system between the source language and the target language causes not all the metaphorical expressions are able to be translated with the equivalent metaphorical expressions; and (3) translation equivalent can be achieved if the translator is able to adjust the translation methods with the type of metaphorical expressions to be translated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it