AN ANALYSIS OF TRANSLATION METHOD USED BY STUDENTS IN TRANSLATING ONLINE NEWSPAPER

MAHARANI, BINTI AMILUDIN (2026) AN ANALYSIS OF TRANSLATION METHOD USED BY STUDENTS IN TRANSLATING ONLINE NEWSPAPER. Diploma thesis, UIN RADEN INTAN LAMPUNG.

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Abstract

ABSTRACT Translation accuracy in international news texts requires the use of appropriate methods, especially for EFL learners who frequently encounter challenges related to syntactic interference, cultural nuances, and contextual meaning. This study aims to identify the translation methods used by third-semester English Education students at UIN Raden Intan Lampung, determine which method is most effective for translating an online newspaper, and examine the difficulties they encounter when translating English online news into Indonesian. This study used a descriptive qualitative design to analyze the translation methods applied by English Education students. The research subjects were an online newspaper text and randomly selected students, with data collected through observation, interviews, and documentation. The researcher served as the primary instrument, supported by triangulation to ensure data validity and credibility. Data was analyzed using the steps of data reduction, data presentation, and drawing conclusions. The findings of this study show that third-semester English Education students at UIN Raden Intan Lampung used various translation methods AI-assisted translation, literal translation, communicative translation, and word-for-word translation with a strong preference for AI tools such as Google Translate, ChatGPT, Cici AI, Quillbot, and DeepL due to their speed and convenience. The analysis further reveals that AI-based translation is the most effective method for translating online news articles, although it still requires manual post-editing to address errors in culturally or politically nuanced contexts. In addition, the students faced several challenges, including difficulty understanding cultural and social meanings in the source text and selecting the most appropriate method for different translation situations, especially since AI tools often fail to capture deeper contextual nuances. In sum, this research reinforces the importance of combining technological assistance with human linguistic competence to ensure high-quality, contextually accurate translations in academic and professional settings.

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