Implementation of Certainty Factor in Expert System for Oil Palm Disease Diagnosis

Abstract

Diseases in palm oil plants are one of the main causes of palm oil production not being maximized, and can even result in crop failure. Farmers need to know the symptoms that occur in oil palm plants in order to diagnose and overcome the diseases that infect the palm oil plants. A system for early detection of disease in palm oil plants is needed in order to prevent a decrease in productivity. An approach that can be used for early diagnosis is an expert system. Expert systems not only provide a diagnosis, but also offer an explanation of the type of disease as well as practical and accurate treatment recommendations. This research applies one of the methods of the certainty factor method to an expert system that combines several symptoms to determine how likely a diagnosis is. This expert system involves 22 symptoms to diagnose six diseases in palm oil plants. The accuracy rate obtained from the application of the expert system with the certainty factor method in diagnosing diseases of oil palm plants based on data from five users shows a result of 100%. This shows that the expert system with the certainty factor method is accurate and can be applied to early detection of diseases that attack palm oil plants.