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Penerapan Forward Chaining dan Certainty Factor Pada Sistem Pendeteksi Penyakit Hewan Qurban Berbasis Android Nabila Tiara Nuraini; Rima Tamara Aldisa; Iskandar Fitri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 1 (2022): Januari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i1.3516

Abstract

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.