Qurbani worship is a worship of the slaughter of livestock carried out on the feast of Eid al-Adha. In Indonesia the dominant livestock used for qurban worship is goats and cows, qurban animals that are allowed to be slaughtered also have conditions ranging from age and most importantly their health. This research is done so that goats and cows that will be slaughtered for qurban worship are free from existing diseases. Some of the problems in the system that will be built is the lack of understanding of the sellers of animals qurban about the diseases suffered by goats and cows from the symptoms experienced by these animals. This study used the method of forward chaining and certaity factor in solving the problems that exist in goat and cow animals, to produce a conclusion in detecting diseases in these animals based on existing symptoms. The process of designing the application of disease detection expert systems in goat and cow animals uses the java programming language and uses a text editor android studio. The authors also tested the comparison of the combination method between forward chaining and certainty factor with the forward chaining and naïve bayes methods that received the highest percentage value results, namely in the forward chaing and certainty factor methods with a value of 9.553%. in scab disease suffered by goat animals and a value of 9.509%in bloating disease suffered by cow animals. Getting the final result on the calculation of detection of goat disease by 91,264% with indicated suffering from scab disease and also in cow animals by 90,432% indicated to suffer from bloating disease, both the final results of the calculation of the type of disease suffered by goats and cows respectively seen from the symptoms that have been inputted by the user.
CITATION STYLE
Nuraini, N. T., Aldisa, R. T., & Fitri, I. (2022). Penerapan Forward Chaining dan Certainty Factor Pada Sistem Pendeteksi Penyakit Hewan Qurban Berbasis Android. JURNAL MEDIA INFORMATIKA BUDIDARMA, 6(1), 154. https://doi.org/10.30865/mib.v6i1.3516
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