Tuti Purwaningsih, Bagus Panuntun, Rochmad Novian Inderanata, Yesih Nurmalasari
Agriculture is an effort in utilizing biological resources made by humans to produce food, industrial raw materials, or energy sources, as well as to manage their environment. One type of agriculture in Indonesia is paddy fields, it wetlands which are usually lower than those of uplands and are used as a place to grow rice. On the other hand, businesses in the agricultural sector are faced with a fairly high risk of uncertainty and the farmers themselves bear the risk. High risks of uncertainty include crop failures caused by climate change such as floods, and drought which are the cause of farmers' losses. To overcome this risk the government provides a solution in the form of the Rice Farmers Business Insurance Program (Asuransi Usaha Tani Padi - AUTP) which ensures farmers get working capital to try to farm from insurance claims. However, to make an insurance claim is not easy which must be in accordance with the procedures of the insurance. This makes it difficult for farmers. So as to facilitate farmers when claiming the AUTP, this research was did. So this research was conducted to be able to classify the image of drought paddy fields, flooded paddy fields, normal paddy fields, and collapsed paddy fields. One method Deep Learning that is currently developing, namely Convolutional Neural Network (CNN). This network is made with the assumption that the input used is an image. This method can make the image learning function more efficient to implement. Based on the results of the classification, obtained training accuracy of 85% and testing by 80%. It can be concluded that the CNN method is able to classify the image of drought paddy fields, flooded paddy fields, normal paddy fields, and paddy fields collapse well. © 2021 School of Engineering, Taylor's University.
Statistics Department, Universitas Islam Indonesia, Indonesia; Management Department, Universitas Islam Indonesia, Indonesia; Doctoral Program in Technology and Vocational Education, Yogyakarta State University, Indonesia; Mechanical Engineering Vocational Education Department, Universitas Sarjanawiyata Tamansiswa, Indonesia
