Sistem Pendeteksi Penyakit Daun Bawang Merah Probolinggo Menggunakan Metode Template Matching Berbasis Raspberry Pi - Moch Zamroni; Hurriyatul Fitriyah; Rizal Maulana (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
By the progress of technology currently is also increasing demand for microcomputer systems that can provide benefits for human life. This system has an important role to help humans, so it is useful for the layman in the field of shallot leaf agriculture. This Embedded system has a camera image capture input of a leek object that will be compared to templates already available in microcomputers, then the value is selected will be processed to the Template Matching method with the specified threshold limit, and will output one of the LED lights which is already available. Therefore, a system is designed to detect the disease of shallot to determine the leaf disease on the shallot. The results of this test show the Logitech C270 camera can take pictures. Based on the results of testing the accuracy of Template Matching method that the amount of 30 data there are 6 results from systems that does not match the actual class. So the accuracy is obtained by 80%. Performance of the system response time has a time value of 15.977 seconds from 30 tests. In this research, a system to detect the disease of shallot using template matching, where the applied method is able to run by what is desired proven by the system can classify the type of leaf disease into purple patch leaf disease, moisture and Moler.