IDENTIFIKASI CITRA IKAN UNTUK MENDETEKSI KESEGARAN IKAN LAUT MENGGUNAKAN METODE HUE SATURATION VALUE DAN K-NEAREST NEIGHBOR - Pertiwi, Marisha; Ramdhani, Nida Mardhiyah; Manik, Agustina Sartika Yos Ekaristi (LPPM UNIVERSITAS BINA INSAN, 2024)
Marine fishery resources contribute to food needs, especially for local communities. The Riau Islands is one of the provinces with abundant marine products but only has 1 fishing port, which can trigger an increase in fish prices in the market and for consumers because the costs incurred by ship owners are getting higher. In addition, it will also cause a decrease in the quality of fish or fish that are not fresh because of the long production chain, which takes a lot of time. Currently, identification of fish freshness is still done manually by fishermen, traders, and consumers. This will certainly make it a little difficult to distinguish between fresh fish and fish that are no longer fresh. One way to recognize and identify fish freshness in the field of informatics is to use image processing. This study will create an image processing system to identify fish freshness using the hue saturation value (HSV) and k-nearest neighbor (K-NN) methods. Based on the results of testing marine fish images, namely mackerel and tuna, which were carried out using the HSV and K-NN methods, it was found that the identification of the quality of freshness of marine fish using the Hue, Saturation, and Value (HSV) color feature extraction was successfully applied with an accuracy value of 100% for the test image of mackerel and 95% for the test image of tuna.