Music comes in many different genres and styles according to it’s content, which is easy for a human listener to distinguish but hard for machine to do. This limitation encourage the creation of a system that can helps machine to classify music genre better. In this graduation paper will be created a system that can classify music genre on Classic, Jazz, Pop, and rock using frequency analysis as feature extraction and ANFIS as classification method.
Result of design are 2 types of ANFIS model which is Model A and Model B. The most accurate model is Model A with average accuracy of 53,33% across all genre. The best model for single genre classification is Model B with 80% accuracy for Classic genre