PENGEMBANGAN SISTEM PAKAR DENGAN METODE NAÏVE BAYES UNTUK DIAGNOSA PENYAKIT BURUNG PUYUH

Development Of An Expert System Using The Naïve Bayes Method For Diagnosing Quail Diseases

Abstract

The increasing need for quail farmers to identify diseases quickly and accurately, considering that many farmers do not have in-depth knowledge about the symptoms of diseases that may occur and the treatments that must be administered once the quails are infected. The lack of veterinarians also causes farmers to be anxious about handling diseases that affect quails. This research aims to develop an expert system that diagnoses quail diseases using the Naïve Bayes method. The methods applied in this study include collecting data on quail disease symptoms, processing data to transform categorical values into numerical ones, and implementing the Naive Bayes algorithm by dividing the dataset into training and testing data. The research results show that the developed model achieved an accuracy of 82.75% in diagnosing quail diseases. This accuracy is quite competitive compared to previous studies that used similar methods for other livestock with accuracy levels ranging from 60% to 90%. The system's performance evaluation using a confusion matrix and classification report indicates that the model can classify most cases correctly, although there are some prediction errors in certain classes. This shows that the effectiveness of the expert system in diagnosing quail diseases using the Naive Bayes method can provide a solution for farmers to recognize and address diseases earlier.