AN ANALYSIS OF PERLOCUTIONARY SPEECH ACTS USED BY THE MAIN CHARACTER ON “WISH DRAGON” MOVIE

Anam, Asroful (2024) AN ANALYSIS OF PERLOCUTIONARY SPEECH ACTS USED BY THE MAIN CHARACTER ON “WISH DRAGON” MOVIE. Skripsi thesis, Universitas Panca Marga.

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Abstract

This research analysis the script of the film "Wish Dragon". The purpose of this research is to find out what type of perlocutionary speech act used by the main character on “Wish Dragon” movie. Perlocutionary speech acts are a form of language that is used in the form of words to carry out an action. In other words, a form of language can be said to be a perlocutionary speech act if the utterance produces an effect or result that is caused by the speaker to the addressee. So, in other words, perlocutionary speech act is carrying out an action by saying something. The scope of this research is pragmatic. The theory used is based on George Yule's theory which explains speech acts. George Yule's theory is used in this research because Geroge Yule explains the types of locutionary, illocutionary and perlocutionary speech acts in more detail and comprehensively. This research is qualitative research with descriptive methods to obtain the data obtained. The data collection technique uses the observation method. Data collection is written documents in the form of text in this research. The source used is a transcript of the film "Wish Dragon". The data analysis method uses the following analysis: first, identifying several words that are included in perlocutionary speech acts. Second, classifying the data that has been obtained based on its type. Third, analyze the data that has been determined based on George Yule's theory which defines the types of perlocutionary types. The results of this research show 13 types included in perlocution from 83 data found in the film wish dragon. Criticism was used 2 data, greeting 10 data, persuading 5 data, sayings were used 9 data, mocking 13 data, saying goodbye 5 data, forgiving 4 data, asking 13 data, complaining 2 data, complaining 5 data, praising 9 data, sarcasm 3 data, and angry 3 data.

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