Pengembangan Aplikasi Mobile Pendeteksi Penyakit Daun Tanaman Jagung dengan Metode Mobile Application Development Life Cycle (MADLC)

Increasing global population growth and food demand have made increasing the production of food crops such as maize a top priority. However, the challenge in maintaining the productivity of these plants is due to foliar diseases which can affect growth and yield. Hence, this research aims to create a mobile app capable of efficiently identifying corn leaf diseases by following the mobile application development life cycle (MADLC) approach. The MADLC methodology serves as a guide in the development of this mobile application. MADLC steps include planning, requirements analysis, design, development, testing, and implementation. The resulting application is designed to run on mobile platforms, enabling farmers and agricultural professionals to easily detect corn leaf disease from their mobile devices. The development of this application aims to gather information about various types of foliar diseases that commonly attack corn plants. In addition, disease detection capabilities are designed and implemented using image processing and artificial intelligence techniques. The test results show that the application can accurately detect several types of leaf diseases in corn from photos taken with a cellphone camera. This research contributes to agriculture and technology by incorporating MADLC principles into the development of mobile applications that support early detection of plant diseases. This application is expected to enable farmers and agricultural actors to detect diseases in corn plants quickly and accurately, enabling early disease control measures and increasing agricultural productivity.