Identifikasi Mutu Buah Pepaya California (Carica Papaya L.) Menggunakan Metode Jaringan Syaraf Tiruan

Abstract

Papaya is one of the fruits that grows in the tropics area, one of the kinds that people’s love the most is papaya California. The quality identification of papaya California fruit can be measured using color, defect, and size. Color, defect and size extracted from image of papaya. The dataset that used in this research are 150 images papaya California. The dataset consist of 3 quality there are good, fair and low. Identification of papaya using the backpropagation neural network method with 17 training function in each training data with 3 different neurons in the hidden layer. The best result of the test is using training function trainrp with 10 neurons is 81,33% for accuracy, 73,37% for precision, and 72% for recall, with 20 neurons is 82,67% for accuracy, 75,24% for precision, and 74% for recall, and with 25 neurons is 80,89% for accuracy, 74,42% for precision, and 71,33% for recall.

Identifikasi Tingkat Kematangan Buah Pepaya Menggunakan Metode Convolutional Neural Network (Cnn)

“…Saat ini para pedagang dan petani buah pepaya masih memantau kematangan pepaya secara manual [3]. Sistem manual yang dimaksud adalah dengan memantau dengan mata manusia dan menerka-nerka dan hanya dengan ditekan-tekan serta dari aromanya saja.…”

The Implementation Of The Fletcher-Reeves Algorithm In Predicting The Growth Of Forest Plant Cultures

“…Therefore, it is essential to direct researchers in predicting the value of planting crops in the following several periods by utilizing the progress and the correct period. Previous researchers said that the Flecther-Reeves algorithm is one of the techniques commonly used to anticipate in artificial neural networks [13,14]. The Fletcher Reeves method is one of the Artificial Neural network methods, a development of the backpropagation algorithm [15,16].…”