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All Journal JURNAL ILMIAH INFORMATIKA
Aditya Bobby Rizki
Universitas Stikubank
Computer Science & IT

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KLASIFIKASI TEKNIK BULUTANGKIS BERDASARKAN POSE DENGAN CONVULUTIONAL NEURAL NETWORK Aditya Bobby Rizki; Eri Zuliarso
JURNAL ILMIAH INFORMATIKA Vol 10 No 02 (2022): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v10i02.5559

Abstract

Convolutional Neural Network (CNN) is a deep learning algorithm which is the development of Multilayer Perception (MLP) which is designed to process data in two-dimensional form. At the stage of making the system there are several stages including sample data, data sources and data analysis methods. The dataset that is processed is the Badminton Technique, namely the Forehand Technique which consists of 374 images, the Service Technique consisting of 369 images and the smash technique consisting of 420 images with outliers of 146 images. After the data is cleaned of outliers, bootrapping is carried out again to unite all data from each separate class into one again. The results of this study say that the Classification of Badminton Techniques Based on Pose with Convolutional Neural Networks, it can be concluded that the process of testing pose classification with test data using several methods such as logistic regression, random forest, and KNN produces significant accuracy. values ranging from 80% to 90%.
Co-Authors Eri Zuliarso