ANALYSIS OF MOOD AND THEME TYPES OF THE MAIN CHARACTER OF THE SIGNALMAN IN THE SHORT STORY ENTITLED THE SIGNALMAN AND THE GHOST AT THE TRIAL BY CHARLES DICKENS (SYSTEMIC FUNCTIONAL LINGUISTICS APPROACH)

PURWATI, INDRAYANI (2019) ANALYSIS OF MOOD AND THEME TYPES OF THE MAIN CHARACTER OF THE SIGNALMAN IN THE SHORT STORY ENTITLED THE SIGNALMAN AND THE GHOST AT THE TRIAL BY CHARLES DICKENS (SYSTEMIC FUNCTIONAL LINGUISTICS APPROACH). Skripsi thesis, Universitas Panca Marga Probolinggo.

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Abstract

The term Metafunctions originated in Systemic Functional Linguistics and is considered to be a property of all languages. Michael Halliday, the founder of Systemic Functional Linguistics, calls these three functions the ideational, interpersonal, and textual. The three metafunctions are mapped onto the structure of the clause. This study analizes the main character’s dialogues of the signalman. The purpose of this study are to describe the mood types and theme types of the main character base on metafunctions by Halliday. The scope of this study is Systemic Functional Linguistics approach. The limitation of this study is the clauses that used by main character in his/her dialogues. This study uses descriptive qualitative research. The sources of the data in this study is the main character’s dialogues. The form of the data taken is in the form text. Meanwhile, the technique of collecting data is documentation. The data analysis method uses Spradley techniques; domain analysis and taxonomy analysis. Then, this study uses re-checking. The result shows that there are ninety seven (97) data. The Mood types found in the data are fifty seven (58,7%) data of Declarative, fourteen (14,4%) data of WH-Interrogative, sixteen (16,4%) data of Polar Interrogative and one (1,5%) data of Imperative. While, the Theme types found in the data are seventy six (78,3%) data of Unmark topical theme, eleven (11,3%) data of Textual theme and one (1,5%) data of Interpersonal theme. As for mark topical theme, there is no data. There is also found nine (9,3%) data of rheme.

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