(Universitas Negeri Malang, Indonesia)(2) Wahyu Tri Handoko
(Universitas Negeri Malang, Indonesia)(3) * Aji Prasetya Wibawa
(Universitas Negeri Malang, Indonesia)(4) Anik Nur Handayani
(Universitas Negeri Malang, Indonesia)(5) Ming Foey Teng
(American University of Sharjah, United Arab Emirates)*corresponding author
AbstractMeasuring the quality of river water used as industrial wastewater disposal is needed to maintain water quality from pollution. The chemical industry produces hazardous waste containing toxic materials and heavy metals. At specific concentrations, industrial waste can result in bacteriological contamination and excessive nutrient load (eutrophication). Using the Convolutional Neural Network (CNN), the method for measuring water quality processes remote sensing images taken via an RGB camera on an Unmanned Aerial Vehicle (UAV). The parameter measured is the change in the color of the river water image caused by the chemical reaction of the heavy metal content of industrial waste disposal. The test results of the Convolutional Neural Network (CNN) method in 2.01s/step obtained the value of training loss mode 17.86%, training accuracy 90.62%, validation loss 23.43%, validation accuracy 83.33%.
KeywordsWastewater, River Water Check, Industrial Pollution, CNN
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DOIhttps://doi.org/10.31763/sitech.v2i2.638 |
Article metrics10.31763/sitech.v2i2.638 Abstract views : 471 |
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