PERANCANGAN APLIKASI UNTUK MENDETEKSI SABUK PENGAMAN MOBIL MENGGUNAKAN ALGORITMA BACKPROPAGATION NEURAL NETWORK (BPNN)

Abdul Jabbar Lubis, Ade Saprin

Abstract


Abstract - To enforce traffic regulations on the highway, police officers face obstacles in monitoring the use of seat belts on cars because cars on the highway are always on the move and almost all cars use window film to avoid the heat of the sun entering the car. Based on the above problems, the authors build a software that can monitor or detect drivers wearing seat belts or not with Microsoft Visual C # 2010. To monitor the use of seat belts, digital cameras are used to conduct image acquisition to be processed by computers. . Furthermore, the image is studied by a system using the Back Propagation Neural Network (BPNN) Artificial Neural Network method as the image of the driver using a seat belt. To make a detection, the test image is input that is the same size as the training image. The test results obtained the level of accuracy for image acquisition with a distance of 1 meter with a similarity using a seat belt with a maximum value of 9% and a degree of similarity without a seat belt of less than 4%.  

Keywords - Image, Neural Network, Backpropagation Algorithm


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References


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DOI: https://doi.org/10.36294/jurti.v2i2.429

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