Application of Naïve Bayes Method for Diagnosing Rubber Tree Diseases at PT. Bridgestone Aek Tarum
DOI:
https://doi.org/10.46229/jifotech.v4i1.876Keywords:
Rubber tree diseases, Expert system, Naïve Bayes, Mobile applicationAbstract
Rubber plant disease attacks roots, stems, tapping areas, and leaves. Factors causing the low rubber plantations are due to limited information and control of rubber tree diseases, so there is a need for a system to improve rubber tree disease control with the help of this system. Currently, without a system, it is only completed by an expert who is considered successful if he is able to make decisions like an expert. Making this system can help an employee in diagnosing diseases in rubber plants. Making this system requires an expert in his field to obtain accurate data regarding information on rubber plant diseases, the data used are 22 symptoms and 7 diseases. In this study the method used is Naive Bayes. The Naive Bayes method works by finding the probability value of the emergence of rubber plant diseases. This application is developed based on Android using the Java programming language in the Android Studio application. From this study it was found that white root fungal disease has 7 symptoms and the choice of confidence level in each symptom is between 0 and 1. Then white root fungal disease has the largest result value, namely 0.0000002911.
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