Melody Difficulty Classification using Frequent Pattern and Inter-Notes Distance Analysis

This research proposes a novel method for melody difficulty classification performed using frequent pattern and inter-notes distance analysis. The Apriori algorithm was used to measure the frequency of notes in note sequence, which length is also included calculation. In addition, analysis level composition based on between successive notes. traditional Javanese compositions known as Gamelan music. Symbolic representation, music sheets were collected dataset, chosen by asking experts divide their into basic, intermediate advanced classes. Then, proposed implemented value each composition. difference interpretation solved calculating mean obtain range values class. Evaluation confusion matrix accuracy, precision recall value, results reaching 82%, 82.1% respectively.