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Suriyati
Software Engineering Technology, Agriculture Polytechnic of Samarinda
Computer Science & IT

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Expert System Diagnosis Disease of Oil Palm Plants Using Forward Chaining and Dempster Shafer Suriyati; Eny Maria; Annafi Franz
TEPIAN Vol 3 No 2 (2022): June 2022
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (444.232 KB) | DOI: 10.51967/tepian.v3i2.773

Abstract

This research is motivated by the problem of inhibiting crop production from oil palm plants, namely disease. Diseases of oil palm plants can be caused by viruses, fungi and, the host plant or an unfavorable environment. The process of diagnosing oil palm plant diseases requires expertise, knowledge and experience. Therefore, this study aims to build an expert system that can diagnose 9 types of plant diseases in oil palm from 29 symptoms based on the knowledge of 1 expert with the forward chaining method of reasoning and the web-based Dempster Shafer calculation method. The testing technique used is black box testing, validation testing, testing and theoretical calculations. The results of the black box test state that the expert system has 100% conformity in terms of functionality. The results of the expert validation test state that the expert system has 100% conformity. The results of the theoretical calculation test state that the expert system calculations are in accordance with the results of manual calculations. The results of the test with a questionnaire based on 32 respondents said it went very well. The results of this study provide the information needed by farmers to be able to diagnose and increase knowledge about how to overcome the problems faced by their oil palm plantations even without direct expert assistance in order to improve quality and stabilize the amount of production according to farmers' expectations.
Expert System Diagnosis Disease of Oil Palm Plants Using Forward Chaining and Dempster Shafer Suriyati; Eny Maria; Annafi Franz
TEPIAN Vol. 3 No. 2 (2022): June 2022
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v3i2.773

Abstract

This research is motivated by the problem of inhibiting crop production from oil palm plants, namely disease. Diseases of oil palm plants can be caused by viruses, fungi and, the host plant or an unfavorable environment. The process of diagnosing oil palm plant diseases requires expertise, knowledge and experience. Therefore, this study aims to build an expert system that can diagnose 9 types of plant diseases in oil palm from 29 symptoms based on the knowledge of 1 expert with the forward chaining method of reasoning and the web-based Dempster Shafer calculation method. The testing technique used is black box testing, validation testing, testing and theoretical calculations. The results of the black box test state that the expert system has 100% conformity in terms of functionality. The results of the expert validation test state that the expert system has 100% conformity. The results of the theoretical calculation test state that the expert system calculations are in accordance with the results of manual calculations. The results of the test with a questionnaire based on 32 respondents said it went very well. The results of this study provide the information needed by farmers to be able to diagnose and increase knowledge about how to overcome the problems faced by their oil palm plantations even without direct expert assistance in order to improve quality and stabilize the amount of production according to farmers' expectations.
Co-Authors Annafi’ Franz Eny Maria