@phdthesis{digilib22203,
           month = {July},
           title = {KLASIFIKASI CITRA DAGING SAPI DAN DAGING BABI
BERDASARKAN CIRI WARNA DAN TEKSTUR},
          school = {UIN SUNAN KALIJAGA YOGYAKARTA},
          author = {NIM. 12650005 WINDA RIZKY ASTUTI},
            year = {2016},
            note = {Dr. Shofwatul ?Uyun, S.T., M.Kom.},
        keywords = {beef, pork, color and texture extraction, classiffication K-NN},
             url = {https://digilib.uin-suka.ac.id/id/eprint/22203/},
        abstract = {The lack of meat in the market make the prices of meat increase
significantly. Many butchers use this situation to get more profit by mixing the
meat. There are some butchers who intentionally mix the beef with pork. Beef and
pork is more easily differentiated by color and texture because of it has slightly
different characteristics, but not all of customer knows the differences about that.
Therefore, researchers will conduct research based on color and texture.
The first step, the researches is performed image acquisition followed by a
pre-processing. The next step is performed RGB color feature extraction and feature
extraction texture of the first order. The results of feature extraction is used to do
the classification using the K-Nearest Neighbour (K-NN). In this researche tested
the combination of feature extraction parameters of color and texture that aims to
determine which combination of parameters that show the best classification
results. Phase analysis was used to find the highest level of accuracy of the
classification results that obtained.
Based on test results, it can be concluded that the combination of feature
extraction parameters that produce high accuracy in image classification of beef
and pork is a combination of parameters mean green color and texture parameters
of entropy with the level of accuracy is about 94 percent and the computation time
is 0,827 second.}
}