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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic
Tika Liana
Informatics Engineering; Universitas Asahan
Computer Science & IT Decision Sciences, Operations Research & Management

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Expert System for Areca Plant Disease Detection Using Forward Chaining Method Muhammad Dedi Irawan; Helmi Fauzi Siregar; Muhammad Yasin Simargolang; Tika Liana
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol 8 No 2 (2020): September 2020
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v8i2.2291

Abstract

Areca palm has been widely planted by the people of the Asahan Regency. This plant is cultivated not only by the farmers, but also by many people living in this regency. Therefore, an expert system is needed to help villagers in detecting areca palm desease. In areca palm cultivation, pests and diseases attack always happen. The purpose of this research is to apply an expert system as a tool to diagnose and also provide advice for control. This expert system, in the form of a consultation scenario, can be done by answering every question (yes or no); all answers are compared to the areca palm plants needs based-on expert experience. The inference method used is forward chaining. The output of this system is the types of diseases, percentages, symptoms, definitions, treatment, and prevention. Keywords: Areca Palm, Expert System, Forward Chaining.
Co-Authors Helmi Fauzi Siregar Muhammad Dedi Irawan Muhammad Yasin Simargolang