Implementasi Metode Dempster-Shafer untuk Diagnosis Penyakit pada Tanaman Kedelai - Rahmat Arbi Wicaksono; Nurul Hidayat; Indriati Indriati (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2018)
Soybean is one of the main sources of food commodities in Indonesia that not only serves as raw materials for the food industry but also non-food industries. But the lack of knowledge of farmers of soybeans crops about the various symptoms and types of diseases that attack soybean plants are problems that have a negative impact on soybean cultivation. Therefore needed a system that can solve problem of soybean disease diagnosis quickly and precisely. In this research, the writer will implement Dempster-shafer method to diagnose soybean plant disease. This soybean plant diagnosis system can detect 5 types of diseases with 16 symptoms. The results of accuracy tested on 25 data cases obtained an accuracy of 92%, so it can be said that the system works well enough and can be applied.