An Appraisal of Attitude of Jacinda Ardern’s Speech on New Zealand Mosque Congregation Shootings
View/ Open
Date
2020Author
Paramitha, Dhara Ayu
Advisor(s)
Zein, T. Thyrhaya
Lubis, Masdiana
Metadata
Show full item recordAbstract
This research entitles An Appraisal of Attitude of Jacinda Ardern’s Speech on New Zealand Mosque Congregation Shootings. The objectives of this research are to identify the types of attitudes devices, to describe the attitude devices that are realized in Jacinda Ardern’s speech, and to explain the attitude that are realized in Jacinda Ardern’s speech. The data of this research were the words, phrases, and sentences. The source of data were Jacinda Ardern’s speech, the Prime Minister of New Zealand. The method used in this research was descriptive qualitative adopted qualiative data analyis procedures proposed interactive model by Miles, Huberman & Saldana, the theory of appraisal attitude from Martin and White. The research limited the study of appraisal attitude. The types of appraisal attitude found in the data were affect with 83 lines (46%), appreciation with 21 lines (30%), judgement with 13 lines (24%). Affect was realized by getting what is related to the speaker and evaluating emotionally about Jacinda Arden as the speaker and the things that was delivered. Appreciation was realized by evaluating the assessment of the speech as the data, while judgement was realized by evaluating the normative assessment of the speaker's behavior relating to rules or conventions of behavior relating to ethics, morals, legal rules, or existing rules. The reason for using appraisal attitude was returning to the function type of appraisal attitude contained in the data. Then, the researcher found the value of the researcher through the theory used. The finding showed that the appraisal attitude utilized in the data was affect, appreciation, and judgement. Affect was the predominant of appraisal attitude used by Jacinda Arden’s speech, while appreciation and judgement were the least ones.
Collections
- Master Theses [240]