PENERAPAN ALGORITMA CONVOLUTIONAL NEURAL NETWORKS (CNN) UNTUK IDENTIFIKASI PENYAKIT PADA TANAMAN CABAI
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Samberi, Berlince
Haris, Abdul
Sangaji, Iriansyah
Haris, Abdul
Sangaji, Iriansyah
Subject
Teknik Informatika
Datestamp
2023-06-20 04:15:34
Abstract :
Diseases of a plant will greatly affect the yield of such a crop. If the disease is not treated immediately, it can damage the crop and result in crop failure which will affect the economy. Therefore, the identification of plant diseases, especially in chili peppers, is very important in the process of plant care. Chili plants are a type of plant that is widely grown in Indonesia, chili plants are also plants that are much loved by almost all people and are one of the food ingredients needed with a lot of demand, it will be necessary to increase chili land. The larger or larger the land area, the greater the effort required to care for and supervise the plants. With the development of technology today, there will be opportunities in identifying plants automatically using a computer system. Using image processing the disease is captured through the camera will be able to be analyzed and identified with a computer. So that in supervising plants will become easier and more efficient. There are several types of diseases in chili plants that are often found, namely yellow virus, stem rot, and leaf spot. A feature of the disease can be seen from the shape of the color of the leaves. In this study, disease identification was carried out using the CNN algorithm. CNN is used so that models can extract features and perform image classification automatically. Image data taken directly from the IP2TL Balitsa plantation of the Ministry of Serpong Jakarta. And the data was taken around 12.30 ? 14.00 noon, so that the image has a clear color. This model will be able to classify 3 types of leaf conditions including 3 diseased and convolutionary processes using Google Colab. This CNN model can produce 45% accuracy
Diseases of a plant will greatly affect the yield of such a crop. If the disease is not treated immediately, it can damage the crop and result in crop failure which will affect the economy. Therefore, the identification of plant diseases, especially in chili peppers, is very important in the process of plant care. Chili plants are a type of plant that is widely grown in Indonesia, chili plants are also plants that are much loved by almost all people and are one of the food ingredients needed with a lot of demand, it will be necessary to increase chili land. The larger or larger the land area, the greater the effort required to care for and supervise the plants. With the development of technology today, there will be opportunities in identifying plants automatically using a computer system. Using image processing the disease is captured through the camera will be able to be analyzed and identified with a computer. So that in supervising plants will become easier and more efficient. There are several types of diseases in chili plants that are often found, namely yellow virus, stem rot, and leaf spot. A feature of the disease can be seen from the shape of the color of the leaves. In this study, disease identification was carried out using the CNN algorithm. CNN is used so that models can extract features and perform image classification automatically. Image data taken directly from the IP2TL Balitsa plantation of the Ministry of Serpong Jakarta. And the data was taken around 12.30 ? 14.00 noon, so that the image has a clear color. This model will be able to classify 3 types of leaf conditions including 3 diseased and convolutionary processes using Google Colab. This CNN model can produce 45% accuracy
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