Optimization of K Parameters on KNN in Gamelan Jegog Title Classification Using Time Domain Features

Abstract

Bali is one of the provinces in Indonesia which has a lot of culture and arts, one of which is the Gamelan Jegog Bali.  The technology nowadays can make it easier for humans to search for the title of a song that was previously unknown. This technology can be applied to the unknown title of Gamelan Jegog. The features used in this system are Short Time Energy and Zero Crossing Rate. The feature is extracted from Gamelan Jegog and then used to find the best k parameter from the K-Nearest Neighbor classifier. The results showed that the highest accuracy was 45% when the k parameter is 9. The amount of data used and the classification method used has an effect on the accuracy of this system when compared to similar studies.