Artificial Intelligence to Hone Musical Ability in Music Learning At the Junior High School Level

Heldisari, Hana Permata (Jurusan Pendidikan Seni Pertunjukan Fakultas Seni Pertunjukan Institut Seni Indonesia Yogyakarta)

Jurnal Pendidikan dan Kajian Seni
Vol 10, No 2 (2025)

The existence of Artificial Intelligence (AI) tools still offers many benefits and advantages. Various  AI tools in the music field such as Soundful, AIVA, Ecrett Music, and Boomy have been proven to help produce a composition but reap pros and cons around copyright as well as the creative process of the creator. This research aims to find out how to use AI in music learning without eliminating creativity or essence from creating a work. This study uses a qualitative approach, namely exploratory research with a type of case study using the Miles and Huberman analysis model, namely data collection, data reduction, data presentation, and conclusion drawn. The object of this study is AIVA as one of the AI products in the field of music. The subjects of this study are 30 students in grade IX of SMP SMPN 6 Yogyakarta. Data collection using in depth interview techniques, non-participant observations, and documentation so that it will be validated using triangulation techniques. Meanwhile, secondary data sources are obtained through documentation in the form of product results using AI. The results of this study state that learning using AI also emphasizes students' skills in the aspect of musical ability from the Music Aptitude Profile (MAP) by Gordon, namely tonal imagery (melody and harmony), rhythm imagery (tempo and meter), and musical sensitivity (phrasing, balance, and style). The learning results obtained produce more creative and harmonious songs because they provide direct experience related to the sensitivity of tone to chords and rhythms produced by AIVA.