KLASIFIKASI TINGKAT KEMATANGAN BUAH PISANG CAVENDISH MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK MODEL VGG-19 - Putro, Aditya Dwi; Amrulloh, Arif (P3M Politeknik Negeri Banjarmasin, 2023)
Bananas found in Cavendish Banana Gardens Purbalingga Regency have different levels of maturity and quality, as a local fruit that has high economic value and has a market potential that is still wide open, Cavendish bananas are one of the most reliable fruit commodities in Indonesia[1]. The government through the National Standardization Agency sets standards for bananas, maintaining the quality of bananas. The purpose of this study was to analyze the influence of light and image quality in classifying the ripeness level of bananas based on the color characteristics of bananas in the Cavendish Banana Garden, Banyumas Regency, Central Java according to SNI 7422:2009[2]. In this study the authors classify the maturity level of cavendish bananas using the Convolutional Neural Network with the Vgg-19 Model, VGG-19 is used to categorize the maturity level of cavendish bananas and the reason for choosing VGG-19 is because VGGNet is deeper and more reliable architecture for ImageNet technology.The author is also interested in learning how accurate the VGG-19 model is. With a total of 9,000 datasets, 80% of which are training data, 10% are validation data, and 10% are test data, The accuracy obtained for epochs 32, 64 and 96 varies. The accuracy results obtained using VGG-19 were 97% at epochs 32, 64 and 96.