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parti astuti, yani
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Computer Science & IT Education

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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

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Expert System for Diagnosing Shallot Plant Diseases Using the Forward Chaining Method Izzul Haq, Dani Ahmad; Parti Astuti, Yani; Yusa Aditama, Daffa
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9084

Abstract

This research aims to develop an expert system with the forward chaining method to diagnose diseases in shallot plants in Mijen District, Demak Regency. The decline in shallot production caused by disease is one of the main problems faced by local farmers. Therefore, this expert system was developed to help farmers diagnose diseases in their crops more quickly and accurately.The research method used combines qualitative and quantitative approaches. Data on plant diseases and symptoms were obtained through interviews with agricultural extension workers and literature review. Based on the data, a knowledge base was built that was used in the expert system. Forward chaining was applied to trace the relationship between symptoms inputted by the user and possible disease diagnoses. The system was tested using validation data, with an accuracy result of 93.3%, indicating that the system has a high level of agreement with the diagnosis provided by the expert.The results of this study show that the developed web-based expert system can provide practical solutions for farmers to diagnose and treat diseases in shallot plants, so as to increase agricultural productivity and reduce losses due to disease attacks. With web-based implementation, this system can be easily accessed by farmers through computer or mobile devices, providing ease of use in the field.
Co-Authors Christy Atika Sari Eko Hari Rachmawanto Izzul Haq, Dani Ahmad Liya Umaroh, Liya Yusa Aditama, Daffa