QUALITY OF CONCEPTUAL METAPHOR IN AUTOMATIC TRANSLATION FEATURE OF POLITICAL HEADLINES BY TEMPO.CO AND KOMPAS TV ON X

This study examines the types of conceptual metaphor of political news headlines of @tempo.co and @KompasTV by automatic translation feature on X using the theory of Lakoff and Johnson (2003). This study aims to analyze the types of conceptual metaphor, identify techniques of translation, and assess quality of translation consisting of accuracy, acceptability, and readability. A qualitative method with a descriptive approach was applied, using content analysis and focus group discussions (FGD) as data collection techniques. The results reveal that there are 100 data containing conceptual metaphor on political news headlines of @tempodotco and @KompasTV. The three types of conceptual metaphor are structural metaphor, ontological metaphor, and ontological metaphor. The most frequent data is ontological metaphor within fifty-six (56) data followed by the commonly used technique, literal translation. The quality of translation shows the score of accuracy is 2.43, acceptability 2.44, and readability 2.49 which indicates these scores are still less accurate, less acceptable and have severe readability issues, which is due to automatic translation feature on X still has limitations in understanding context, language, and culture.