Klasifikasi Citra Dalam Identifikasi Jeruk Nipis dan Jeruk Mandarin Menggunakan Convolutional Neural Network (CNN)
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Nov 22, 2024
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Abstract
With the rapid development of technology in the field of image processing, it really helps farmers in identifying types of citrus fruit. This research aims to identify the differences between limes (Citrus aurantiifolia) and mandarin oranges (Citrus reticulata) using image processing methods and morphological analysis. Image processing is carried out to analyze visual differences based on color, texture and fruit size. In addition, chemical analysis was carried out to differentiate the composition of the compounds contained in the two types of oranges. The research results show that this approach is able to identify the differences between limes and mandarins with a high level of accuracy, and can be applied in various industries, including agriculture and food processing.
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Saputra, R., Erlanda, H., & Ramadhanu, A. (2024). Klasifikasi Citra Dalam Identifikasi Jeruk Nipis dan Jeruk Mandarin Menggunakan Convolutional Neural Network (CNN). JITSI : Jurnal Ilmiah Teknologi Sistem Informasi, 5(4), 213 - 218. https://doi.org/10.62527/jitsi.5.4.282
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References
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3. Cahyono, R., & Sari, M. (2021). Analisis Kandungan Nutrisi pada Jeruk. Jurnal Gizi Tropis, 11(1), 102-108.
4. Dewi, R. et al. (2022). Vitamin C dan Antioksidan pada Jeruk. Jurnal Biologi Tropika, 15(4), 130-137.
5. Fadhilah, A. et al. (2020). Uji Organoleptik Jeruk Nipis dan Mandarin. Jurnal Teknologi Pangan, 8(1), 45-52.'
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7. Ahmad, Z., & Hidayat, T. (2020). Kandungan Kimia dan Manfaat Kesehatan dari Buah Jeruk. Jurnal Agrikultur Indonesia, 15(2), 123-130.
8. Susanto, R., & Wulandari, A. (2019). Analisis Morfologi dan Kimia pada Varietas Jeruk. Jurnal Biologi Tropika, 12(3), 98-107.
9. Suryani, S., et al. (2022). "Nutritional and Health Benefits of Citrus Aurantiifolia." Journal of Nutritional Science, 11(3), 215-228.
10. Hasan, M., et al. (2021). "Morphological and Chemical Characteristics of Citrus Reticulata." International Journal of Agriculture and Food Research, 12(2), 113-126.
11. Zhang, Y., et al. (2020). "Comparative Study on Vitamin C Content in Citrus Fruits." Food Chemistry, 315, 126-134.
12. Lee, J., et al. (2023). "The Impact of Citrus Aurantiifolia on Immune System Enhancement." Journal of Functional Foods, 54, 142-150.
13. Kumar, P., et al. (2019). "Health Benefits and Nutritional Values of Mandarin Oranges." Journal of Medicinal Food, 22(4), 354-361.
14. Ali, M., et al. (2022). "Antioxidant Properties of Citrus Fruits and Their Potential Health Benefits." Antioxidants, 11(1), 32-45.
15. Smith, R., et al. (2021). "Comparison of Flavonoid and Carotenoid Content in Citrus Fruits." Plant Foods for Human Nutrition, 76(1), 58-65.
16. Chen, L., et al. (2020). "Role of Citrus Fruits in Cardiovascular Health." Journal of Cardiovascular Research, 89(5), 223-230.
17. Thompson, A., et al. (2022). "Dietary Fiber Content in Citrus Fruits and Its Health Implications." Nutritional Research Reviews, 35(2), 88-97.
18. Patel, R., et al. (2021). "Nutritional Comparison of Citrus Aurantiifolia and Citrus Reticulata." Journal of Food Science and Technology, 58(7), 2923-2931.
19. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
20. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep Learning. Nature, 521(7553), 436-444.
21. Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). ImageNet Classification with Deep Convolutional Neural Networks. Advances in Neural Information Processing Systems, 25, 1097-1105.
22. Russakovsky, O., & Fei-Fei, L. (2015). ImageNet Large Scale Visual Recognition Challenge. International Journal of Computer Vision, 115(3), 211-252.
23. Redmon, J., Divvala, S., & Girshick, R. (2016). You Only Look Once: Unified, Real-Time Object Detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 779-788.