Aplikasi Machine Learning untuk Mendeteksi Kematangan Tomat menggunakan Metode Backpropagation
DOI:
https://doi.org/10.30588/jeemm.v8i1.1815Keywords:
Machine Learning, Tomato, Image Extraction, BackpropagationAbstract
The rapid development of artificial intelligence has now been widely used in various industrial fields, with various benefits that make it easier, speed up work processes, automate and be efficient in resources to improve cyber security and can be implemented easily and of course will continue to be developed further, such as In the agricultural industry, artificial intelligence can be used to identify certain types of fruit or plant leaves and their level of maturity. This research will create a machine learning application to identify the level of ripeness of tomatoes with 3 types of tomatoes, old tomatoes, young tomatoes and rotten tomatoes. From each type of tomato there are 50 object images in the form of images in .jpg format, of which 15 object images are used as training data and 35 images as test data to detect tomato images using the Backpropagation method which will utilize image feature extraction in the form of RGB colors. The results obtained from testing images of young, old and rotten tomatoes obtained an accuracy rate of 83%.
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