Open AccessIMAGE PROCESSING BASED TILAPIA SORTATION SYSTEM USING NA
Author(s) -
Sukenda Sukenda,
Ari Purno Wahyu,
Benny Yustim,
Sunjana Sunjana,
Yan Puspitarani
Publication year - 2021
Publication title -
jitter (jurnal ilmiah teknologi informasi terapan)/jitter
Language(s) - English
Resource type - Journals
eISSN - 2686-0333
pISSN - 2407-3911
DOI - 10.33197/jitter.vol7.iss1.2020.459
Subject(s) - tilapia , naive bayes classifier , fish <actinopterygii> , fishery , histogram , artificial intelligence , computer science , biology , image (mathematics) , support vector machine
Tilapia has a value of export quality and is imported from America and Europe, tilapia is cultivated in freshwater, the largest tilapia producing areas are Java and Bali for the export market in the Middle East, value fish with a size of 250 grams / head (4 fish / kg ) in their intact form is in great demand. According to news circulating, fish of this size in the Middle East are ordered to meet the consumption of workers from Asia. the fish classification process is a very difficult process to find the quality value of the fish to be sold to meet export quality. Fish classification techniques can use the GLCM technique (Gray Level Oc-Currance Matrix) classification using images of fish critters with the GLCM method.The fish image data is analyzed based on the value of Attribute, Energy, Homogenity, Correlation, Contrash, from the attribute the density data matrix is ??generated for each. Fish image data and displayed in the form of a histogram, the data from the GLCM results are then classified with the Naive Bayes algorithm, from the results of the classification of data taken from 3 types of tilapia from the types of gift, Red, and Blue.