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All Journal Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi
Irene Oktaviani Duka
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Computer Science & IT

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Identifikasi Penyakit Tanaman Citra Daun Cabe Menggunakan Gray Level Co-Occurrencce Matrix Dan Support Vector Machine Irene Oktaviani Duka; Huan Arthur Ado; Yampi R.Kaesmetan
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 2 No. 2 (2024): Mei : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v2i2.86

Abstract

Disease control of chili leaf citra plants is an important aspect in modern agriculture to increase crop yields and reduce losses due to pest attacks on chili leaf citra plants. In this research, identification of chili leaf diseases uses Gray Level Co-Occurrence to obtain image features, and the Support Vector Machine (SVM) method is used to classify the feature extraction results according to leaf disease categories in the test image. Based on the disease class using the test image. .As a classification tool for identifying plant pests in images of chili leaves, the dataset used in this research consists of images of leaves that represent normal conditions and conditions attacked by pests. The pest identification process consists of several stages, including image pre-processing, feature extraction, as well as training and testing. SVM model.
Co-Authors Huan Arthur Ado Yampi R.Kaesmetan