Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
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This Author published in this journals
All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Rizki Oktavinus Tarigan
STMIK Kaputama
Automotive Engineering Computer Science & IT Control & Systems Engineering

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Design And Development Of Karo Traditional Music Instrument Recognition Application Based On Digital Image Using Convolutional Neural Network Method Rizki Oktavinus Tarigan; Achmad Fauzi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.348

Abstract

In this modern era, multimedia technology has role important in various field like education, health, and publications. Thesis This focused on development application introduction tool music traditional Karo tribe based digital image use Convolutional Neural Network (CNN) method. Karo music has characteristic typical unique and important for culture of North Sumatra. Study This use method Squeezenet and MobileNetV2 for compare accuracy in introduction object tool music Karo tribe. The Convolutional Neural Network (CNN) method is used in the introduction process. Steps covers convolution, function Activation ReLU, pooling, layers connected full, and the output layer with function Activation Soft max. Image data tool music Karo tribe gathered from Google Images. System This own steps like preprocessing image, model training with CNN method, and analysis results training. Research results This give comparison accuracy between method Squeezenet and MobileNetV2 in recognize tool music Karo tribe. Supporting data used in analysis, especially image tool music obtained Karo tribe from Google Images, with structured design and implementation of CNN, applications This succeed recognize type tool music with level good accuracy.
Co-Authors Fauzi, Achmad