@phdthesis{digilib50468,
           month = {May},
           title = {KLASIFIKASI TELUR FERTIL DAN INFERTIL
PADA CITRA CANDLING TELUR ITIK MAGELANG
MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR (KNN)},
          school = {UIN SUNAN KALIJAGA YOGYAKARTA},
          author = {NIM.: 16650078 Yulia Siti Ambarwati},
            year = {2020},
            note = {Pembimbing: Dr. Shofwatul ?Uyun, S.T., M.Kom},
        keywords = {Itik Magelang, Citra Candling, Telur Fertil, Variance Threshold, KNN},
             url = {https://digilib.uin-suka.ac.id/id/eprint/50468/},
        abstract = {Magelang ducks as one of the leading cattle in Central Java that has the best
egg quality is a promising commodity for poultry farmers. To increase the
productivity of Magelang ducks, candling is an important process for sorting fertile
and infertile eggs. However, the manual candling process is limited to the accuracy
of human vision. Therefore, researchers want to utilize technology in the process of
duck egg candling that subsequently classified using a computer.
The research began with image acquisition. The next step is pre-processing
the image by cropping, resizing, and segmenting with the triangle threshold
followed by the extraction of the color, shape, and Gray Level Co-ocurrence Matrix
(GLCM) texture features. After normalizing the results of feature extraction, then
perform the feature selection using the variance threshold method. Then classify
the relevant features using the KNN algorithm. This study aims to choose the best
features of the best classification performance. The analysis is to find the highest
solution and the fastest time in the classification process.
The results of this study showed the highest accuracy of 92.31\% and the
classification time of 0.008 seconds on features: green, roundness, variance, and std
at the value of k = 5.}
}