@thesis{thesis,
		author={Nasution  Deby Rizka Afrilia},
		title ={The Evaluation of Donald Trump’s Emotional Speech: Appraisal Analysis and Acoustic Phonetics},
		year={2018},
		url={},
		abstract={This research titled ?The Evaluation of Donald Trump?s Emotional Speech: Appraisal Analysis and Acoustic Phonetics?. It analyzed Donald Trump speech based on scientific science using Appraisal theory on Attitude devices to analyze the text and using Praat to support the findings emotion in word of feeling based on sound of Donald Trump. The research used Martin and White examined the emotional conditions contained in Trump's speech transcription by using Attitude devices: Affect, Judgment and Appreciation and using Praat version 6.0.41 for Windows for the detection and analysis emotion of speech. The data of this research was the transcript and the sound from Donald Trump's speech on the 72nd Session of the United Nations General Assembly. The research focused on a specific sentence addressed to North Korea showing Donald Trump emotion. The researcher examined the emotional conditions contained in Trump's speech by using Attitude devices: Affect, Judgment and Appreciation. Then, using Praat which consisted of an algorithmic approach for the detection and analysis of normal, angry and panic emotion from sound by using Praat seen on the range of Pitch and Intensity. This research was conducted with qualitative descriptive approach. The findings of Attitude showed the results the number of Affect to 30.3%, Judgment to 45.5% and Appreciation 24.2%. The findings of Praat analysis showed that at Affection 6 words (16.6%) Pitch and Intensity showed angry emotion, and 5 words (13.8%) Pitch showed angry emotion and Intensity showed panic emotion. At Judgment 10 words (27.7%) Pitch and Intensity showed angry emotion and 5 words (13.8%) Pitch showed angry emotion and Intensity panic emotion. At Appreciation 6 words (16.6%) Pitch and Intensity showed angry emotion, 3 words (8.3%) Pitch showed angry emotion and Intensity showed panic, and 1 words (2.7%) Pitch showed angry emotion and Pitch showed normal emotion.}
		}