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Dewi Kristina
Fakultas Hukum Universitas Brawijaya
Computer Science & IT Decision Sciences, Operations Research & Management

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Expert System Diagnosing Diseases in Aglaonema Plants Using the Dempster Shafer Method Kristina, Dewi; Simanjorang, R. Mahdalena
Login : Jurnal Teknologi Komputer Vol. 17 No. 02 (2023): Jurnal Teknologi Komputer, Edition Desember 2023
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/login.v17i02.93

Abstract

Aglaonema is an ornamental plant called Sri Fortune or Chinese Evergreen. This plant grows well in the tropics. One of the common problems in aglaonema plants is the emergence of diseases that cause plant damage. So we need an expert system that can help the community to diagnose the disease as an initial treatment in disease control. The expert system was built using the Dempster Shafer method by entering disease data and symptoms which aims to determine the disease experienced by the Aglaonema plant without having to manually diagnose. The results showed how the process of calculating the initial combination rule to the last combination rule was based on the selected symptoms, so it could be concluded that the highest density value was Bacterial Stem Rot disease with a density value of 0.8881 or 88.81%.
Expert System Diagnosing Diseases in Aglaonema Plants Using the Dempster Shafer Method Kristina, Dewi; Simanjorang, R. Mahdalena
Login : Jurnal Teknologi Komputer Vol. 17 No. 02 (2023): Jurnal Teknologi Komputer, Edition Desember 2023
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/login.v17i02.93

Abstract

Aglaonema is an ornamental plant called Sri Fortune or Chinese Evergreen. This plant grows well in the tropics. One of the common problems in aglaonema plants is the emergence of diseases that cause plant damage. So we need an expert system that can help the community to diagnose the disease as an initial treatment in disease control. The expert system was built using the Dempster Shafer method by entering disease data and symptoms which aims to determine the disease experienced by the Aglaonema plant without having to manually diagnose. The results showed how the process of calculating the initial combination rule to the last combination rule was based on the selected symptoms, so it could be concluded that the highest density value was Bacterial Stem Rot disease with a density value of 0.8881 or 88.81%.
Co-Authors Simanjorang, R. Mahdalena