Implementasi Teknologi Image Processing Untuk Identifikasi Pengukuran Bobot Ikan Hias Dalam Penentuan Jumlah Pakan
DOI:
https://doi.org/10.33504/jitt.v2i2.195Keywords:
Goldfish, Image processing, Image segmentationAbstract
Goldfish (Carassius Auratus) is a beloved ornamental fish among enthusiasts. In the care of Goldfish, feeding plays a crucial role in supporting their growth, thus the feed provided must correspond to the size, quantity, and nutritional content required by the fish. One way to determine the appropriate amount of feed is by measuring the fish's weight. However, conventional measurements may suffer inaccuracies due to several factors, such as the observer's skill level and the tendency of fish to move. The aim of this research is to develop a system capable of determining the feed amount for the fish based on their weight. In this study, the Author utilizes image processing technology using image segmentation techniques to measure the weight of ornamental fish in determining the appropriate feed quantity. Based on test results, this system can measure weight by simultaneously placing Goldfish in an aquarium, resulting in length accuracy of 88.57%, width of 86.18%, and weight of 86.61%, determining feed quantity at 85.87% accuracy with a feed difference of 1.64 grams. Meanwhile, measuring individual fish/tails produces length accuracy of 92.96%, width of 77.15%, and weight of 94.12%, as well as feed quantity determination at 99.43% accuracy with a feed difference of 0.08 grams.
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