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Matondang, Zekson
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Computer Science & IT Decision Sciences, Operations Research & Management

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Design of an Expert System Application for Disease Diagnosis in Burley Tobacco Plants Based on Android using the Backward Chaining Method Damanik, Romanus; Sinuraya, Bersama; Matondang, Zekson; Silitonga, Parasian D.P
Bahasa Indonesia Vol 15 No 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i02.158

Abstract

Tobacco is cultivated through a series of special processes, which is a very important crop in industry due to its significant impact on the economy. Making seeds, soil preparation, planting, care, up to the harvest phase, and post-harvest processing are all tasks included in this stage. These plants often show various signs of disease during their life cycle, which can seriously worsen if not treated quickly. In situations like these, effective solutions are needed to find and nip the problem in the bud. An expert system application has been developed in recent research to overcome this problem. This system relies on the backward chaining method, a clever technique for diagnosing diseases in tobacco plants. With this method, the application tries to search and find facts that match the current data to set the right diagnostic goals. This research not only allows users to better diagnose diseases in tobacco plants, but also helps develop prevention strategies so that similar diseases do not appear again in the future.
Co-Authors Romanus Damanik Silitonga, Parasian D.P Sinuraya, Bersama