Design And Development Of Karo Traditional Music Instrument Recognition Application Based On Digital Image Using Convolutional Neural Network Method


  • Rizki Oktavinus Tarigan STMIK Kaputama
  • Achmad Fauzi STMIK Kaputama



Application_Introduction, Traditional_Musical_Tools, Suku_Karo, Citra_Digital, CNN


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.


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L. Novia and D. Zalilludin, "Aplication of Learning Media to Know Traditional Musical Instruments for Children Based on Augmented Reality on Mobile Devices," J. IKRA-ITH Inform. , vol. 5, no. 1, pp. 15–21, 2020.

EN Arrofiqoh and H. Harintaka, "Implementation of the Convolutional Neural Network Method for Plant Classification in High Resolution Imagery," Geomatics , vol. 24, no. 2, p. 61, 2018, doi: 10.24895/jig.2018.24-2.810.

SE Sitepu and A. Ardoni, "Cultural Information of the Karo Tribe of North Sumatra," Inf. library. and Archives , vol. 8, no. 1, p. 413, 2019, doi: 10.24036/107314-0934.

V. Nur, Hidayat & Maarif, “Evolution Journal Volume 6 No 2 |,” Perenc. WAREHOUSE LAYOUT USING Method. CLASS-BASED STORAGE- Cr. ON Distribut. Comput. off. equip. Hidayat , vol. 6, no. 2, pp. 36–42, 2018.

J. Jumadi, Y. Yupianti, and D. Sartika, "Digital Image Processing for Object Identification Using Hierarchical Agglomerative Clustering Methods," JST (Journal of Science and Technology , vol. 10, no. 2, pp. 148– 156, 2021, doi: 10.23887/jstundiksha.v10i2.33636.

A. Fadjeri, "Digital Image Processing to Calculate Extraction of Greenbean Characteristics of Robusta and Arabica Coffee (Case Study: Temanggung Coffee)," Indones. J. Appl. Informatics , vol. 4, no. 2, p. 92, 2020, doi: 10.20961/ijai.v4i2.39253.

Heriyanto, "Modified or Unmodified Bitmap Image Analysis by Combining Pixel RGB (Red Green Blue) and Histogram Deviation Methods," Semin. Nas. inform. 2013 (semnasIF 2013) , vol. 2013, no. semnasIF, pp. 72–80, 2013.

B. Hardiansyah, AP Armin, and AB Yunanda, "Image Reconstruction at Super Resolution Using Bicubic Interpolation," INTEGER J. Inf. Technol. , vol. 4, no. 2, pp. 1–12, 2019, doi: 10.31284/j.integer.2019.v4i2.684.

AN Hidayat, EY Eka, FM Abdullah, M. Akbar, and P. Rosyani, "Analysis of the Development of Artificial Intelligence in the Game Industry," JATIMIKA J. Kreat. Mhs. inform. , vol. 2, pp. 118–120, 2021.

N. Nufus et al. , “System for Detection of Pedestrians in Limited Environments Based on MobileNet V2 SSDs Using Normalized 360° Images,” Pros. Monday. Nas. Techno Science. and Inov. Indonesia. , vol. 3, no. November, pp. 123–134, 2021, doi: 10.54706/senastindo.v3.2021.123.

A. Raup, W. Ridwan, Y. Khoeriyah, S. Supiana, and QY Zaqiah, "Deep Learning and Its Application in Learning," JIIP - J. Ilm. Educator Science. , vol. 5, no. 9, pp. 3258–3267, 2022, doi: 10.54371/jiip.v5i9.805.

F. Angga Irawan, M. Sudarma, and D. Care Khrisne, "Design and Development of Applications for Identification of Android-Based California Papaya Plant Diseases Using the Cnn Method Squeezenet Architecture Model," J. SPEKTRUM , vol. 8, no. 2, p. 18, 2021, doi: 10.24843/spektrum.2021.v08.i02.p3.

F. Zaelani and Y. Miftahuddin, "Comparison of EfficientNetB3 and MobileNetV2 Methods for Identification of Fruit Types Using Leaf Features," J. Ilm. Technol. Applied Information. , vol. 9, no. 1, pp. 1–11, 2022, doi: 10.33197/jitter.vol9.iss1.2022.911.

AE Wijaya, W. Swastika, and OH Kelana, "Implementation of Transfer Learning in Convolutional Neural Networks for Diagnosis of Covid-19 and Pneumonia in X-Ray Imagery," Sainsbertek J. Ilm. Techno Science. , vol. 2, no. 1, pp. 10–15, 2021, doi: 10.33479/sb.v2i1.125.

RMR Clinton and S. Sengkey, “Traffic Violation List System Prototype,” J. Tek. Electrical and Computer. Vol.8 , vol. 8, no. 3, pp. 181–192, 2019.




How to Cite

Tarigan, R. O., & Achmad Fauzi. (2023). Design And Development Of Karo Traditional Music Instrument Recognition Application Based On Digital Image Using Convolutional Neural Network Method. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 3(1), 422–427.