Banana Pest And Disease Expert System Using Forward Chaining and Certainty Factor

Abstract

Farmers do not understand the various forms of banana plant illnesses. In addition, the inadequate guidance offered by agricultural instructors to banana farmers also leads to issues such as crop failure. Considering these issues requires an expert system capable of aiding farmers in identifying and diagnosing banana pests and diseases. The inference techniques implemented in constructing this expert system are forward chaining and certainty factor. The research process comprises the following phases: (1) acquisition of data; (2) forward chaining inference; (3) weighting of symptoms; and (4) development of expert systems. The banana’s pests and diseases expert system has yielded ten distinct diseases and pests, each characterized by 37 symptoms. Data processing employs forward chaining to generate decision trees and perform pruning to establish criteria for determining symptom statements. The combined certainty computation yields a percentage value of 97.25875968% with a significant confidence level