Research
Universitas Malikussaleh
System visuals are confidential under client NDA
Overview
Knowledge-based expert system for vannamei shrimp disease diagnosis using Naive Bayes and Certainty Factor methods — supporting academic research.
Tech Stack
- Python
- Flask
- scikit-learn
- MySQL
Problem
Manual diagnosis of vannamei shrimp diseases requires high expertise and lengthy processes. Farmers and researchers struggle to identify diseases based on symptoms without a knowledge-based system.
Solution
An expert system was developed using Naive Bayes for disease classification and Certainty Factor to measure diagnostic confidence. The system accepts symptom input, processes the knowledge base, and produces diagnosis with confidence levels.
Impact
Researchers can perform more structured and faster diagnostic analysis. The system output supports decision-making and serves as a reference for further aquaculture research.
Key Features
- Shrimp disease symptom input
- Naive Bayes classification
- Certainty Factor scoring
- Disease knowledge base
- Diagnosis history
- Report export
Highlights
2 knowledge-based analysis methods
Structured symptoms & confidence levels
Output supports academic research
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