Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Aditya Dimas
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
EEG Analysis of Emotional Responses to Classical Piano Music : Comparing Professional Pianists and Non-Musicians Aditya Dimas; Ari Sugiharto
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 3 No. 1 (2025): Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v3i1.416

Abstract

This study aimed to explore the impact of classical piano music on emotional responses among professional pianists compared to non-professionals. The piano, known for its extensive pitch range and dynamic versatility, serves as a pivotal instrument in both classical and popular music. Previous research has examined how music influences individual’s styles and behaviors. In our investigation, we analyzed electroencephalogram (EEG) signals to assess emotional responses in both groups, employing coherence measures. Listening tests were conducted to evaluate the effects of pitch and dynamics on emotional characteristics. Findings revealed that all ten emotional categories were significantly influenced by variations in pitch and dynamics. Specifically, emotions such as Happy, Romantic, Comic, Calm, Mysterious, and Shy generally increased with pitch, though a decline was observed at the highest pitches. Conversely, Heroic, Angry, and Sad emotions tended to decrease with rising pitch levels, while Scary emotions were pronounced at extreme low and high pitches. Regarding dynamics, emotions like Heroic, Comic, Angry, and Scary were more intense with loud notes, whereas Romantic, Calm, Mysterious, Shy, and Sad emotions were enhanced with softer notes. Notably, the emotion Happy showed no sensitivity to dynamic changes. These results provide valuable insights into the quantification of emotional characteristics associated with piano music.
Co-Authors Ari Sugiharto