Music is closely related to human psychology, this fact indicates that music can be associated with specific emotions and mood in humans. Any music that has been created has its own mood that radiates, and therefore has a lot of research in the field of Music Information Retrieval (MIR) has been developed to explore the mood of the music. This research resulted in a classification system of music on mood by using K-Nearest Neighbor algorithm. The system uses the data input in the form of music file formats mono * .wav in the refrain lasts 30 seconds, which in turn make the process of classification of music by using K-NN algorithm. The system generates output in the form of labels mood, contentment, Exuberance, depression and anxious. In general the results of the accuracy of the system by using K-NN is good enough ie 86.55% on the value of k = 3, and the processing time classification of the average 0.01021 seconds perfile of music. Index Term : Music, Mood, Classification, K-NN Intisari-Musik erat kaitannya dengan psikologi manusia, kenyataan ini mengindikasikan bahwa musik dapat terkait dengan emosi dan mood/ suasana hati tertentu pada manusia. Setiap musik yang telah tercipta memiliki mood tersendiri yang terpancar, maka dari itu telah banyak penelitian dalam bidang Music Information Retrieval (MIR) yang telah dilakukan untuk pengenalan mood terhadap musik. Penelitian ini menghasilkan sebuah sistem pengelompokan musik terhadap suasana hati dengan menggunakan algoritma K-Nearest Neighbor. Sistem menerima masukan data berupa file musik format mono *.wav, yang selanjutnya melakukan proses pengelompokan terhadap musik dengan mengggunakan klasifikasi K-NN. Sistem menghasilkan keluaran berupa label jenis mood yaitu, contentment/ kepuasan, exuberance/ gembira, depression/ depresi dan anxious/ cemas; kalut. Secara umum hasil akurasi sistem dengan menggunakan algoritma klasifikasi K-NN cukup baik yaitu 86,55% pada nilai k = 3, serta waktu pemrosesan klasifikasi rata-rata 0,01021 detik per-file musik.
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