Klasifikasi Telur Fertil Dan Infertil Menggunakan Ekstraksi Ciri Gray Level Co-Occurrence Matrix Dan Artificial Neural Network (Studi Kasus: Independent Breeders)
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Institusion
Institut Teknologi Telkom Purwokerto
Author
Diva, Aditya Pratama
Subject
T Technology (General)
Datestamp
2021-12-10 08:33:41
Abstract :
Independent Breeders is an independent business engaged in animal husbandry, especially hatching eggs, hatching eggs carried out by Independent Breeders is duck eggs. In hatching eggs there is a process that must be done, namely the candling process. The candling process is the observation of eggs to determine if the eggs are fertile or infertile. Temperature stability in the hatching process is very important so that the process of candling must be done quickly. Therefore, an effort is needed to help the egg candling process to minimize egg failure. The Artificial Neural Network (ANN) method has been widely applied in various fields, one of which is in the field of animal husbandry, ANN can be used to classify fertile and infertile eggs based on egg embryos. In this study, a system was developed that was able to classify egg fertility using Artificial Neural Network (ANN) and GLCM as feature extraction. Based on the tests that have been carried out, it can be concluded that the system can classify eggs into fertile and infertile classes with an accuracy of 96.65%. Keywords : Egg hatching, ann, duck egg
Independent Breeders is an independent business engaged in animal husbandry, especially hatching eggs, hatching eggs carried out by Independent Breeders is duck eggs. In hatching eggs there is a process that must be done, namely the candling process. The candling process is the observation of eggs to determine if the eggs are fertile or infertile. Temperature stability in the hatching process is very important so that the process of candling must be done quickly. Therefore, an effort is needed to help the egg candling process to minimize egg failure. The Artificial Neural Network (ANN) method has been widely applied in various fields, one of which is in the field of animal husbandry, ANN can be used to classify fertile and infertile eggs based on egg embryos. In this study, a system was developed that was able to classify egg fertility using Artificial Neural Network (ANN) and GLCM as feature extraction. Based on the tests that have been carried out, it can be concluded that the system can classify eggs into fertile and infertile classes with an accuracy of 96.65%. Keywords : Egg hatching, ann, duck egg
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