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KLASIFIKASI EMOSI MUSIK BERDASARKAN FITUR AUDIO DENGAN MENGGUNAKAN METODE FUZZY K NEAREST NEIGHBOR

KURNIAWAN, REZA TRIADI (2019) KLASIFIKASI EMOSI MUSIK BERDASARKAN FITUR AUDIO DENGAN MENGGUNAKAN METODE FUZZY K NEAREST NEIGHBOR. Bachelors Degree (S1) thesis, University of Muhammadiyah Malang.

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Abstract

Music is full of unique attributes, especially concerning auditory perceptions. Amplitude elements, frequency and duration cannot be discerned yet as music to human ears. Before those three elements processed by human brains interpretation so that they became timbre pitch dynamics and tempo. In the process of music interpretation in the fields of musicology, there is also the term “emotion” that’s often used. Every music listener have their own segments, their own preference, depending on the emotion and the character of the listener. At 1989, Robert E. Thayer proposed a two dimensional model of the mood and emotion (of the music) through his research. The aforementioned model is hoped to be able to used as a reference in terms of sorting music based by their mood. The objective of this research is the classification of music samples by using their audio features through the usage of Fuzzy KNN method. There will be four mood categories used at this research, namely Anger, Happy, Calm and Sad. Extraction of “energy”, ‘tonality” and “tempo” will be done using the library of Matlab MIRToolbox. Aforementioned “MIRToolbox” is a library collection, excelled in the processing of unique attributes in music, in the perspective of Music Information Retrieval. Generally the classification results of audio features used in the aforementioned software, is satisfactory, as long as the K parameter is correct. Fuzzy system is added in order to count the membership degree of the samples.

Item Type: Thesis (Bachelors Degree (S1))
Student ID: 201210370311195
Corporate Creators: HARDIANTO WIBOWO (0723028801), WILDAN SUHARSO (0730038405)
Keywords: Classification, Music, Mood, Audio Features, Fuzzy KNN
Subjects: B Philosophy. Psychology. Religion > BF Psychology
M Music and Books on Music > M Music
Q Science > Q Science (General)
T Technology > TN Mining engineering. Metallurgy
Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Divisions: Faculty of Engineering > Department of Informatics (55201)
Depositing User: 201210370311195
Date Deposited: 24 Aug 2019 09:20
Last Modified: 24 Aug 2019 09:20
URI : http://eprints.umm.ac.id/id/eprint/51572

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