ANALISIS PENGENALAN NADA GITAR
MENGGUNAKAN METODE KLASIFIKASI DYNAMIC TIME
WARPING (DTW) BERBASIS MATLAB
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Institusion
INSTITUT TEKNOLOGI DIRGANTARA ADISUTJIPTO
Author
MULYADI, RIAN
Subject
T Technology (General)
Datestamp
2024-05-30 01:47:18
Abstract :
Tone is a regular sound and has a certain single frequency. Tone. Basically there are 7 notes that consist of A, B, C, D, E, F and G. The problem often faced in music is not knowing the character of nad aitu itself so that it will be difficult to play music. From this problem, the final project entitled `` analysis of guitar tone recognition using the matlab-based Dynamic Time Warping (DTW) classification method 'was made so that students could recognize the characteristics of notes in music. In analyzing this tone, the writer uses the Dynamic Time Warping (DTW) method. It starts with reference data and test data which both have the same process, which starts with sound recording, preprocessing, and feature extraction. Then the results of the two feature extractions are compared using the Dynamic Time Warping (DTW) classification method. The result of the DTW comparison is the output with the smallest value. This study found that the highest success rate in this study was 100% and the average recognition accuracy was 82.5%. The results were obtained from 40 tests on each guitar tone consisting of tone A, tone B, tone C and tone D.
Tone is a regular sound and has a certain single frequency. Tone. Basically there are 7 notes that consist of A, B, C, D, E, F and G. The problem often faced in music is not knowing the character of nad aitu itself so that it will be difficult to play music. From this problem, the final project entitled `` analysis of guitar tone recognition using the matlab-based Dynamic Time Warping (DTW) classification method 'was made so that students could recognize the characteristics of notes in music. In analyzing this tone, the writer uses the Dynamic Time Warping (DTW) method. It starts with reference data and test data which both have the same process, which starts with sound recording, preprocessing, and feature extraction. Then the results of the two feature extractions are compared using the Dynamic Time Warping (DTW) classification method. The result of the DTW comparison is the output with the smallest value. This study found that the highest success rate in this study was 100% and the average recognition accuracy was 82.5%. The results were obtained from 40 tests on each guitar tone consisting of tone A, tone B, tone C and tone D.
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