Tone Classification Matches Kodàly Handsign with the K-Nearest Neighbor Method at Leap Motion Controller

  • Muhammad Croassacipto Institut Teknologi Nasional - ITENAS
  • Muhammad Ichwan Institut Teknologi Nasional - ITENAS
  • Dina Budhi Utami Institut Teknologi Nasional - ITENAS
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Abstract

Hands can produce a variety of poses in which each pose can have a meaning or purpose that can be used as a form of communication determined according to a general agreement or who communicate. Hand pose can be used as human interaction with the computer is faster, intuitive, and in line with the natural function of the human body called Handsign. One of them is Kodàly Handsign, made by a Hungarian composer named Zoltán Kodály, which is a concept in music education in Hungary. This hand sign is used in interactive angklung performances in determining the tone that will be played by the K-Nearest Neighbor (KNN) algorithm classification process based on hand poses. This classification process is performed on the extracted data from Leap Motion Controller, which takes Pitch, Roll, and Yaw values based on basic aircraft principle. The results of the research were conducted five times with the value of k periodically 1,3,5,7,9 with test data consisting pose of 874 Do', 702 Si, 913 La, 612 Sol, 661 Fa, 526 Mi, 891 Re, and 1004 Do punctuation on 21099 training data. The test results can recognize hand poses with the optimal k value k=1 with an accuracy level of 94.87%.

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Author Biographies

Muhammad Croassacipto, Institut Teknologi Nasional - ITENAS
Scholar
Muhammad Ichwan, Institut Teknologi Nasional - ITENAS
Lecturer
Dina Budhi Utami, Institut Teknologi Nasional - ITENAS
Lecturer

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Published
2020-06-10
How to Cite
Croassacipto, M., Ichwan, M., & Utami, D. B. (2020). Tone Classification Matches Kodàly Handsign with the K-Nearest Neighbor Method at Leap Motion Controller. International Journal on Information and Communication Technology (IJoICT), 5(2), 40-45. https://doi.org/10.21108/IJOICT.2019.52.283
Section
Computational Science