Expert System for Disease Identification in Palawija Plants with the Dempster Shafer Method

Wanda Ilham (Department of Informatic Engineering, Catur Insan Cendekia University Cirebon)
Sapta Eka Putra (Department of Retail Management, Tamansiswa University of Padang)
Dasril Aldo (Department of Informatics, Institut Teknologi Telkom Purwokerto)
Yohani Setiya Rafika Nur (Department of Informatics, Institut Teknologi Telkom Purwokerto)
Annisaa Utami (Department of Informatics, Institut Teknologi Telkom Purwokerto)

Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering)
Vol 10 No 2 (2023): List of the Accepted Article for Future Issues

Crops, including corn, are important agricultural commodities and contribute greatly to people's food needs. Diseases in crops are often the main factor that reduces crop production and quality. Maize plants are particularly susceptible to various pests and diseases, such as Leaf Blight, Leaf Spot, Rust, Stem Blight, Anthracnose, Root Rot, Cob Rot, Smut, Mosaic Virus, and Nematodes. Unfortunately, farmers often use pesticides or inappropriate control methods, resulting in suboptimal care and the emergence of new pests or diseases. This study aims to assist farmers in detecting early symptoms of pests and diseases in corn plants, so that control can be more precise and effective. In this study, 10 disease attack data were processed using the Dempster Shafer method. This method processes data based on symptoms seen in corn plants, allowing detection of types of pests and diseases and recommendations for handling them with an accuracy rate of about 80%. Therefore, the Dempster Shafer method is relevant for use in the identification of diseases in corn plants.