KLASIFIKASI TINGKAT KESEGARAN DAGING SAPI MENGGUNAKAN METODE NAÃVE BAYES DAN EKSTRAKSI WARNA HEU SATURATION VALUE
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Nabila, Aurel
Palupiningsih, Pritasari
Putra, Rakhmadi Irfansyah
Palupiningsih, Pritasari
Putra, Rakhmadi Irfansyah
Subject
Teknik Informatika
Datestamp
2022-09-27 02:24:38
Abstract :
Fresh beef has a high content, but if the beef is allowed to stand for a long time it will have an impact on existing reserves. Therefore, consumers must understand about fresh beef with cold beef. One way to determine the level of freshness of beef in the information field is by using image processing. This research will create an image processing system to determine the freshness of beef using the HSV method, and Naïve Bayes. The HSV method is used for the extraction of color features in beef images, and the Naïve Bayes method is spent to classify the meat into two classes, fresh and cold. The purpose of this research is to summarize the results of this method in classifying beef freshness. The results of this study indicate an achievement rate of 80%.
Fresh beef has a high content, but if the beef is allowed to stand for a long time it will have an impact on existing reserves. Therefore, consumers must understand about fresh beef with cold beef. One way to determine the level of freshness of beef in the information field is by using image processing. This research will create an image processing system to determine the freshness of beef using the HSV method, and Naïve Bayes. The HSV method is used for the extraction of color features in beef images, and the Naïve Bayes method is spent to classify the meat into two classes, fresh and cold. The purpose of this research is to summarize the results of this method in classifying beef freshness. The results of this study indicate an achievement rate of 80%.
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