Yudhistiro, Kukuh, Fatah, Gatot Suharto Abdul, Wibawa, Lasinta Ari Nendra and Prastiyono, Yudi (2023) Detection of aflatoxin contamination in corn using the Simplified Gabor Wavelet algorithm. IOTA Internet of Things and Artificial Intelligence Journal, 3 (1). pp. 19-32. ISSN 2774-4353

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Abstract

The quality of corn is essential to determine whether the corn is still suitable for consumption and what type of corn it is. Corn is one type of vegetable that is indispensable for the nutritional needs of the Indonesian people today and is a mixture of other essential ingredients. Corn is rich in fiber, which is good for improving digestion and overcoming constipation, controlling blood sugar levels, maintaining heart health, overcoming depression, maintaining eye health, and preventing diverticulitis. In this research, image recognition is used to determine and detect the content of aflatoxin, which is one type of abnormality or disorder in corn. This affects the quality of corn, whether corn is suitable for human consumption, and what impact aflatoxin has on the human body. on testing using parameters Non UV image, SGW Filter Image θ = 0, 90, 180 and 270, and The resulting SGW image with the number of orientations N = 4, θ = θ + pi/N, and θ = θ + 2*pi/N, The aflatoxin content in humans can cause carcinogenic or liver cancer and acute necrosis, cirrhosis, and carcinoma in the animal liver.

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