Implementation of Decision Tree Algorithm in Expert System for Diagnosing Rice Plant Diseases

Michael Hutapea; Edi; Robby Wijaya

doi:10.59934/jaiea.v5i1.1633

Authors

Michael Hutapea STMIK Time
Edi STMIK Time
Robby Wijaya STMIK Time

DOI:

https://doi.org/10.59934/jaiea.v5i1.1633

Keywords:

Decision Tree, Expert System, Rice Disease, Diagnosis, web

Abstract

Rice plants are a major agricultural commodity that are vulnerable to disease attacks. Errors or delays in diagnosis can lead to significant losses for farmers. This study aims to develop a web-based expert system for diagnosing rice plant diseases using the Decision Tree algorithm. The system is based on 20 symptom data and 8 types of diseases. The development is carried out using PHP programming language and MySQL database. System testing on 8 real cases showed an accuracy level of 100%. These results indicate that the Decision Tree algorithm is effective in expert systems for diagnosing rice plant diseases quickly and accurately.

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