Sistem Klasifikasi Musik Gamelan Angklung Bali Terhadap Suasana Hati Menggunakan Algoritma K-Nearest Neighbor Berbasis Algoritma Genetika
Abstract
Balinese gamelan angklung instrumental music through its sound waves can interfere the waves of human’s thought to decrease brain’s wave frequency. The aim is to affect the psychological condition in term of mood so it will lead to positive stress level with either low or high energy. Music with positive stress level and low energy level is categorized as contentment. Positive stress level music and high energy level is categorized as exuberance. MIR (Music Information Retrieval) is a part of Data Mining which digging information about music’s data. One of them is the mood’s classification which is interpreted by chunks of music data. This research designs and builds the classification system to detect the Balinese gamelan angklung instrumental music’s mood using K-NN algorithm and K-NN based Genetic Algorithm. K-NN is able to overcome the classification problem well. However, behind its excellence, the very sensitive k value setting becomes a weakness. Applying Genetic Algorithm on the K-NN classification system optimizes the optimal k value’s determination. Based on the same training and testing data set, K-NN gives 81,08% (k=6) as the highest accuracy percentage, while K-NN based Genetic Algorithm gives 89,19% (k=4) as the highest accuracy percentage.
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This work is licensed under a Creative Commons Attribution 4.0 International License
