Deteksi Kualitas Telur Menggunakan Analisis Tekstur
Abstract: Currently to find
out the quality of eggs was conducted on visual observation directly on the
egg, both the outside of the egg in the form of eggshell conditions or the
inside of the egg by watching out using sunlight or a flashlight. This method
requires good accuracy, so in the process it can affect results that are not
always accurate. This is due to the physical limitations of each individual is
different. This study examines the utilization of digital image processing for
the detection of egg quality using eggshell image.
The feature extraction method performed
a texture feature based on the histogram that is the average intensity,
standard deviation, skewness, energy, entropy, and smoothness properties. The
detection method for training and
testing is K-Means Clustering algorithm.
The results of this application are able to help the user to determine
the quality of good chicken eggs and good quality chicken eggs, with accurate
introduction of good quality eggs by 90% and poor quality eggs by 80%.
Keywords: eggs, energy,
entropy, texture analysis, K-Means, mean, skewness, standard deviation
intensity, smoothness
Penulis: Enny Itje Sela, M
Ihsan
Kode Jurnal: jptinformatikadd170003
