| dc.description.abstract | Goats are among the livestock commonly chosen for Qurban due to their more affordable price compared to cows. Selecting goats that meet the requirements for Qurban is a crucial aspect of performing the sacrificial ritual in accordance with Islamic law. This research develops a classification and selection system for goats suitable for Qurban by integrating the Naïve Bayes method and the Evaluation Based on Distance from Average Solution (EDAS) method. The Naïve Bayes method is used for classifying the health condition of the goats, while the EDAS method is utilized to rank the goats based on criteria such as age, weight, and health condition. The dataset used in this study was obtained from Arjuna Farm and includes data on 500 goats. Data augmentation was performed to expand the dataset to 2,000 goats with variations in age, weight, and health condition. Using the 2,000 goat dataset implemented in the system, 30 new data tests were conducted. The test results show that the combination of these two methods provides good performance. The Naïve Bayes model successfully classified the data with an accuracy of 89.75%, a precision of 90.5%, a recall of 89.75%, and an F1-score of 90%. Meanwhile, the EDAS method was able to produce accurate rankings, with the best goat being 3 years old, weighing 40 kg, having an 84.87% probability of good health, and an EDAS score of 2.0389139847. This model will be implemented in a web-based application to facilitate relevant parties in classifying and ranking goats. | en_US |
