Open AccessExpert System Diagnosing Disease of Honey Guava Using Bayes Method
Author(s) -
Dahlan Abdullah,
Muhammad Zarlis,
Akim Manaor Hara Pardede,
Apipah Anum,
Rini Suryani,
Parwito,
Permata Ika Hidayati,
Edi Susilo,
Danur Azissah Roesliana Sofais,
Elsa Rosyidah,
Sara Surya,
Akbar Iskandar,
_ Darmawansyah,
Titin Aprilatutini,
Cut Ita Erliana,
Didik Setiyadi
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1361/1/012054
Subject(s) - computer science , expert system , sql server , bayes' theorem , table (database) , knowledge base , sql , plant disease , database , data mining , artificial intelligence , microbiology and biotechnology , bayesian probability , biology
Honey Guava Fruit (Green Guava Deli) is one of the fruit that are very popular, liked, and consumed by the people. The pProblems that cause a decline in the quality of guava due to honey guava plants can also be attacked by disease. The limited access information about honey guava disease is one of the obstacles, while the number of agricultural experts is still insufficient. In this study a media system will built with an expert system approach. The application development phase begins with the system analysis stage, namely data analysis and system requirements description, building a knowledge base, Data Flow Diagram, Entity Relationship Diagram, and creating a table structure, table design, and interface menu design. After the design phase is complete, it is continued to the implementation and testing phase of the application. This application uses Visual basic. Net as a programming language and Sql Server as a database. The research was conducted to make Honey Guava Disease Diagnosis System Expert System software that can work like an agricultural expert. The system is able to diagnose as many as 3 diseases using the Bayes Theorem method.