The Expert System for Diagnosing Pest and Disease in Pineapple Plant Using the Iterative Deepening Search (IDS) Method on the Android Platform
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Abstract
This research was conducted to design and develop pineapple pests and diseases diagnosis expert system with Iterative Deepening Search (IDS). This expert system runs on android platform. The certainty factor of this expert system is initialized by an expert and the final certainty factor is computed by the system. The data used in this expert system consist of 5 types of pineapple pests, 6 types of pineapple diseases. 31 types of symptoms and 11 types of rules are used to diagnose pineapple pests and diseases. To validate this expert system, two types of tests were conducted, which are expert system verification and system evaluation by users. Expert system verification was conducted by comparing 10 results from the diagnosis system and the results of the diagnosis by an expert. The compare result shows that the expert system result 100% is similar to the result of the expert. To evaluate the system, 30 respondents were asked to evaluate using questionnaires, which were grouped into three groups, i.e. group I (pineapple experts), group II (pineapple farmers and agriculture students) and group III (computer science students). All three stated this expert system runs well (75.56%, 72.44%, and 79.83% respectively).
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