Dimas  Fiqh Puskoaji, Tito  Waluyo Purboyo, Randy  Erfa Saputra, 
    A Experiment of Reccurent Neural Network Methods for Generating a Music,
    Journal of Engineering and Applied Sciences,
    Volume 15,Issue 12,
    2020,
    Pages 2619-2622,
    ISSN 1816-949x,
    jeasci.2020.2619.2622,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2020.2619.2622)
    Abstract: Music is a composed sound so that it contains
rhythm, song and harmony. Every music has different
chord provisions and arrangements which makes making
music difficult. Based on these problems, a solution was
made in the form of Music Generation with the Recurrent
Neural Network (RNN) method to facilitate the making of
a music. Recurrent Neural Network (RNN) is a class of
artificial neural networks where the connection between
nodes forms a directed graph along the sequence. This
allows it to show temporary dynamic behavior for a time
sequence. The data used is in the form of a Musical
Instrument Digital Interface (MIDI) format file with
sufficient amounts. The system will produce a midi file
that has undergone the process of making chords and
merging randomly, so that, it becomes a new music. Then
implemented in Python. The output in this system
produces a music that allows it to be processed again in
the Digital Audio Workstation (DAW) to produce the
desired music.
    Keywords: Music Generation;Recurrent Neural Network (RNN);Python;music;MIDI