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All Journal Jurnal Teknologi Pertanian Internet of Things and Artificial Intelligence Journal
Gatot Suharto Abdul Fatah
Balai Penelitian Tanaman Tembakau dan Serat, Malang
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Journal : Internet of Things and Artificial Intelligence Journal

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Detection of aflatoxin contamination in corn using The Simplified Gabor Wavelet algorithm Yudistiro, Kukuh; Fatah, Gatot Suharto Abdul; Wibawa, Lasinta Ari Nendra; Prastiyono, Yudi
Internet of Things and Artificial Intelligence Journal Vol. 3 No. 1 (2023): Vol. 3 No.1 (2023): Volume 3 Issue 1, 2023 [February]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v3i1.576

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.
Fertilization Technology of Virginia Tobacco Farmers in Bojonegoro and Lamongan Districts and approach to IoT Supriyadi, Supriyadi; Fatah, Gatot Suharto Abdul; Putri, Rumanintya Lisaria; Yogi, Yoga Angangga
Internet of Things and Artificial Intelligence Journal Vol. 3 No. 1 (2023): Vol. 3 No.1 (2023): Volume 3 Issue 1, 2023 [February]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v3i1.582

Abstract

The districts of Jember, Bojonegoro, and Lamongan are home to Virginia tobacco shops. In Bojonegoro Regency, there are 11,522 ha and 11,517 ha of tobacco land, while there are 6697 ha and 6683 ha in Lamongan Regency. The quality of tobacco is lowered by excessive fertilization, the use of impure varieties, interplanting with chilies, and the neglectful pruning of shoots (Tirtosastro S and Taufik I, 2022). Inorganic fertilizers used in excess will deteriorate unhealthful soil (Arifin Z and Lolita ES, 2020). The issue of excessive chlorine fertilizer use results in a decrease in tobacco quality (low burning power, dull color). The Bojonegoro and Lamongan regions have lost many tobacco product industries as a result of excessive chlorine fertilizer restrictions on tobacco plants. Based on the aforementioned issues, a survey study on fertilization methods for Virginia farmers in the Bojonegoro and Lamongan Regencies is required. The goal of this study was to ascertain how fertilizers were applied by farmers and to measure the soil's and tobacco leaves' chlorine contents. The fertilization process is carried out with an approach to the Internet of Things which is necessary for fertilization automation and more optimal results.
Co-Authors Abi D. Hastono Lasinta Ari Nendra Wibawa Musthofa Lutfi Prastiyono, Yudi Puji Widodo Rumanintya Lisaria Putri, Rumanintya Lisaria Soebandi soebandi Soebandi Soebandi Supriyadi Supriyadi Yogi, Yoga Angangga Yudistiro, Kukuh