Sistem Identifikasi Kondisi Tanaman Padi Berdasarkan Warna Daun Menggunakan Algoritma Learning Vector Quantization
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Pambudi, Renaldy Bagas Bayu
Haris, Abdul
ziza, Rosida Nur A
Haris, Abdul
ziza, Rosida Nur A
Subject
Teknik Informatika
Datestamp
2022-09-26 06:38:35
Abstract :
Rice is the main staple for Indonesians and Indonesia is one of the largest rice producing countries in Asia.Farmers must be able to know whether the rice plant is healthy, that theoretically review and farmers still use his instincts as a direct observation. One of the main nutrients indispensable for rice plants is Nitrogen (N) fertilizer to support the growth of rice plants, the insufficient content causes the growth and development of a plant to be not optimal. By utilizing information technology in agriculture, especially rice plants need their rice crop condition identification system based on the color of rice leaves, so as to help farmers to facilitate the farmers in monitoring the health of rice farmers and also make easy in knowing the nitrogen fertilizer requirements contained in rice leaves. Learning Vector quantization method to calculate the Euclidean distance between the initial weight with training data, so that at the end of the epoch will find the weight of the end of each class. The initial step in implementing this method to collect training data 25 are divided into five classes that are stored in the database and 25 test data. The data is in the form of digital images that have been processed in a system by resizing, RGB to HSV transformation and canny edge detection to obtain patterns from the rice leaf image. The data is in the form of digital images that have been processed in a system by resizing, RGB to HSV transformation and canny edge detection to obtain patterns from the rice leaf image. Testing the results of the learning vector quantization method with confusion matrix obtained an accuracy value of 85.31%, a precision value of 86.53% and a recall value of 85.39%.
Rice is the main staple for Indonesians and Indonesia is one of the largest rice producing countries in Asia.Farmers must be able to know whether the rice plant is healthy, that theoretically review and farmers still use his instincts as a direct observation. One of the main nutrients indispensable for rice plants is Nitrogen (N) fertilizer to support the growth of rice plants, the insufficient content causes the growth and development of a plant to be not optimal. By utilizing information technology in agriculture, especially rice plants need their rice crop condition identification system based on the color of rice leaves, so as to help farmers to facilitate the farmers in monitoring the health of rice farmers and also make easy in knowing the nitrogen fertilizer requirements contained in rice leaves. Learning Vector quantization method to calculate the Euclidean distance between the initial weight with training data, so that at the end of the epoch will find the weight of the end of each class. The initial step in implementing this method to collect training data 25 are divided into five classes that are stored in the database and 25 test data. The data is in the form of digital images that have been processed in a system by resizing, RGB to HSV transformation and canny edge detection to obtain patterns from the rice leaf image. The data is in the form of digital images that have been processed in a system by resizing, RGB to HSV transformation and canny edge detection to obtain patterns from the rice leaf image. Testing the results of the learning vector quantization method with confusion matrix obtained an accuracy value of 85.31%, a precision value of 86.53% and a recall value of 85.39%.
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