Identifikasi penyakit pada foliage tanaman cendana menggunakan algoritma ID3 berdasarkan fitur GLCM dan Color Moment

Krisantus Jumarto Tey Seran; Budiman Baso

doi:10.24246/aiti.v22i1.73-83

Authors

Krisantus Jumarto Tey Seran Program Studi Teknologi Informasi, Fakultas Pertanian Sains dan Kesehatan Universitas Timor https://orcid.org/0000-0002-6600-507X
Budiman Baso Program Studi Teknologi Informasi, Fakultas Pertanian Sains dan Kesehatan Universitas Timor

DOI:

https://doi.org/10.24246/aiti.v22i1.73-83

Keywords:

Sandalwood leaf, GLCM, color moment, color, ID3 algorithm

Abstract

The main cause of the decreased economic value of sandalwood trees is disease. There are several ways to detect (identify) diseases in sandalwood trees, one of which is through the leaves. One way to identify the disease is by observing the color and shape of the leaves affected by the disease using image processing or computer vision. In this study, the GLCM feature is combined with the Color Moment feature to analyze the disease of the Sandalwood leaves, especially the mean value of each RGB in the Sandalwood leaf image. The ID3 algorithm is chosen as a learning method to analyze texture and color extraction data to determine the type of disease. The data testing results showed an accuracy level of 92.31% when the GLCM feature is combined with the Color Moment feature. It indicates that the combination of these features provides good results in detecting and classifying the type of disease in Sandalwood leaves.

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