Claim Missing Document
Check
Articles

Found 12 Documents
Search

Model pengalihbahasaan buku teks bidang ekonomi dan keuangan berbahasa Inggris ke bahasa Indonesia: analisis akurasi terjemahan buku marketing management dan fundamentals of financial management Ade Sukma Mulya; Ina Sukaesih; Nur Hasyim
Jurnal Linguistik Terapan JLT Volume 5 No 1, 2015
Publisher : UPT P2M Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Tujuan penelitian ini adalah menyusun model penerjemahan untuk buku teks bidang ekonomi dari bahasa Inggris ke dalam bahasa Indonesia. Pada tahun pertama, penelitian diarahkan pada Analisis produk terjemahan untuk mengetahui kualitas terjemahan. Penelitian ini menggunakan pendekatan deskriptif kualitatif dengan kasus ganda. Analisis konten digunakan terhadap data yang diperoleh dari dokumen (buku teks Marketing Management dan Fundamentals of Financial Management), hasil kuesioner dan interview mendalam dengan informan. Temuan yang diperoleh pada tahun pertama menghasilkan model terjemahan yang meliputi bahasa sumber, proses penerjemahan yang mencakup kesepadanan pesan dan penggunaan ideologi, metode dan teknik penerjemahan, output (hasil terjemahan dalam bahasa sasaran), dan outcome (kualitas terjemahan) yang mencakup keakuratan, keberterimaan dan keterbacaan. Analisis terhadap aspek keakuratan memperlihatkan bahwa terjemahan buku teks Marketing Management sebagian besar akurat.
Investigating Romantic-Tone Transfers in the Human Translation Compared to AI Subtitling: A Case Study of the Dilan 1990 Film Rakhmi, Fanny Puji; Abdillah, Taufik Eryadi; Humolungo, Farizka; Sukaesih, Ina; Indrayani, Septina
Journal of Language and Literature Studies Vol. 6 No. 1 (2026): March
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/jolls.v6i1.3570

Abstract

This paper examines how romantic tone is carried across languages in film subtitling, where text must be brief, well-timed, and easy to read. We focus on Dilan 1990, a popular Indonesian teen romance known for playful, indirect lines that rely on inference and rhythm. Today, many studios generate first-pass subtitles with neural machine translation and then rely on human post-editors to refine style and timing. We ask how well AI handles this kind of subtle, affect-rich dialogue and where human editing still adds value. We compare 24 well-known lines addressed by Dilan to Milea in two versions: the official English subtitles and outputs produced by ChatGPT under the same line-level constraints. Using a practical set of translation techniques (e.g., modulation, compression, adaptation) and a tone rubric (playfulness/coyness, warmth, persona/rhythm), we perform a line-by-line analysis. The human subtitles tend to keep implicature and pace through concise, idiomatic choices that fit character and reading speed. The AI versions are fluent but more likely to explain subtext or lengthen the line, which can blunt teasing and shift the scene’s mood. AI can match human choices when the source line is already compact and direct. Where meaning depends on ellipsis, metaphor, and micro-timing, human post-editing remains crucial. We close with practical guidelines for NMT-plus-post-editing workflows in romance subtitling.