PENGENALAN CITRA JENIS PENYAKIT TUMBUHAN SELADA MENGGUNAKAN EKSTRAKSI FITUR COLOR CHANNEL DAN GRAY LEVEL CO-OCCURENCE MATRIX
Total View This Week0
Total View This Week0
Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Jannah, Miftahul
Luqman, Luqman
Widiyanto, Max Teja Ajie Cipta
Luqman, Luqman
Widiyanto, Max Teja Ajie Cipta
Subject
Teknik Informatika
Datestamp
2023-06-26 06:18:02
Abstract :
Lettuce is a plant found in Indonesia which is also widely found in traditional markets and supermarkets. Lettuce also includes vegetables that are much favored by the community, lettuce has fresh green leaves, contains high enough nutrients and mineral content. Lettuce is often used as a basic ingredient for salads or as a complement to ready?to-eat foods, lettuce can also be grown in the lowlands and highlands. This study aims to computerize the disease process in lettuce by applying the Gray Level Co-occurrence Matrix (GLCM) method. The method is a statistical method that can be used to analyze feature extraction. After extracting the characteristics of each lollo verde lettuce disease, the next step is classification. The lettuce disease will be classified according to a predetermined category. At the calcification stage using the K-Nearest Neighbor (KNN) method. The data tested in the form of lettuce lollo verde in jpg format as many as 9 data and the accuracy obtained is 77%
Lettuce is a plant found in Indonesia which is also widely found in traditional markets and supermarkets. Lettuce also includes vegetables that are much favored by the community, lettuce has fresh green leaves, contains high enough nutrients and mineral content. Lettuce is often used as a basic ingredient for salads or as a complement to ready?to-eat foods, lettuce can also be grown in the lowlands and highlands. This study aims to computerize the disease process in lettuce by applying the Gray Level Co-occurrence Matrix (GLCM) method. The method is a statistical method that can be used to analyze feature extraction. After extracting the characteristics of each lollo verde lettuce disease, the next step is classification. The lettuce disease will be classified according to a predetermined category. At the calcification stage using the K-Nearest Neighbor (KNN) method. The data tested in the form of lettuce lollo verde in jpg format as many as 9 data and the accuracy obtained is 77%
Download
book
BibTex
Latex, Jabref
cloud_download
Original Resource
url resource Institution
