In this research, an image classification model was developed to distinguish hand objects display scissors, rock, and paper using one of the image classification methods in the form of a Convolutional Neural Network (CNN). There are eight steps involved in determining the legibility of an image when an image file is recognized by uploading it from the computer's internal storage. The eight stages are source data retrieval, INGBAS data categorization, data visualization, import library using the Convolutional Neural Network (CNN) algorithm, data training, data accuracy and validation, image prediction, and conclusions. Based on the testing in this study, the average value of accuracy is 90%.
Copyrights © 2023