Penerapan Neural Network Dalam Klasifikasi Citra Permainan Batu Kertas Gunting dengan Probabilistic Neural Network


  • Siti Julianita Siregar * Mail STMIK Triguna Dharma, Medan, Indonesia
  • Ahmadi Irmansyah Lubis STMIK Triguna Dharma, Medan, Indonesia
  • Erika Fahmi Ginting STMIK Triguna Dharma, Medan, Indonesia
  • (*) Corresponding Author
Keywords: Classification; Image Processing; Rock Paper Scissors Game; Neural Network; Probabilistic Neural Network

Abstract

In this research, an image classification model was developed to distinguish hand objects pointing at rock, paper, and scissors using one of the popular image classification methods, namely the Probabilistic Neural Network. Probabilistic Neural Network is a method in an artificial neural network that is used to classify a category based on the results of calculating the distance between the density function and the probability. PNN has 4 stages of processing, namely Input Layer, Pattern Layer, Summation Layer, and Output Layer. Tests in the study were carried out with a total of 60 testing data from three object classes from the dataset. Then the results of the classification of Batu, Scissors, and Paper hand images using the application of the PNN algorithm in this research test obtained an average accuracy value of 90%

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Article History
Submitted: 2021-12-22
Published: 2021-12-31
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How to Cite
Siregar, S. J., Lubis, A. I., & Ginting, E. F. (2021). Penerapan Neural Network Dalam Klasifikasi Citra Permainan Batu Kertas Gunting dengan Probabilistic Neural Network. Building of Informatics, Technology and Science (BITS), 3(3), 420-425. https://doi.org/10.47065/bits.v3i3.1143
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