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All Journal Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering)
Yohani Setiya Rafika Nur
Department of Informatics, Institut Teknologi Telkom Purwokerto
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Expert System for Disease Identification in Palawija Plants with the Dempster Shafer Method Wanda Ilham; Sapta Eka Putra; Dasril Aldo; Yohani Setiya Rafika Nur; Annisaa Utami
Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Vol 10 No 2 (2023): List of the Accepted Article for Future Issues
Publisher : Jurusan Teknik Elektro, Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/jurnalecotipe.v10i2.4418

Abstract

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.
Co-Authors Annisaa Utami Dasril Aldo Sapta Eka Putra Wanda Ilham