Automatic music classification for Dangdut and campursari using Naïve Bayes

Music classification can be performed by classifying music according to its genre, style, mood, and others. Various methods have been implemented to automatically classify music. Naïve Bayes learning algorithm is one of the most efficient and effective classification algorithm. Dangdut and campursari music are the music often heard by Indonesian. But the classification of dangdut and campursari music is still rarely performed. In this study, we perform automatic music classification for dangdut and campursari music. We use Naïve Bayes to classify music and the data was discretized based on Minimum Description Length Principle (MDLP). We used jSymbolic to extract feature from MIDI files. Currently, we use 45 features that are included in the category of instruments and pitch. This experiment produced the accuracy of 85.14%.