Abstrak
Starfruit (Averrhoa carambola L.) is a horticultural commodity with potential for development in export markets. However, manual postharvest sorting may result in errors and inconsistencies in determining fruit ripeness and size. This study aims to develop an automatic system for detecting the ripeness and size of starfruit using an ESP32-CAM, a weight sensor (load cell and HX711), a Convolutional Neural Network (CNN) algorithm, and the Internet of Things (IoT). The system determines the size category based on fruit weight according to SNI 4491:2009, while fruit images are processed using a CNN to classify ripeness into three categories: unripe, partially ripe, and fully ripe. The classification results are transmitted in real time via Telegram. Testing on 30 samples showed that the CNN achieved an accuracy of 86.6%, while the load cell sensor produced an average measurement error of approximately 1–2%. These results indicate that the system is capable of automatically sorting starfruit based on ripeness and size while enabling remote monitoring of the results. The system has the potential to improve sorting consistency and support starfruit quality management in accordance with established standards.
Referensi
Benkeblia, N. (2018). Unlocking the full potential of carambola (Averrhoa carambola) as a food source: Botany, growing, physiology and postharvest technology. In Agriculture, food, and food security: Some contemporary global issues (pp. 131–158). Nova Science Publishers.
Bhaskar, B., & Shantaram, M. (2013). Morphological and biochemical characteristics of Averrhoa fruits. International Journal of Pharmaceutical, Chemical & Biological Sciences, 3(3), 924.
Fan, Y., Sahu, S. K., Yang, T., Mu, W., Wei, J., Cheng, L., . . . Liu, H. (2020). Dissecting the genome of star fruit (Averrhoa carambola L.). Horticulture Research, 7. https://doi.org/10.1038/s41438-020-0306-4
Hetharua, A. D., Sumarno, S., Gunawan, I., Hartama, D., & Kirana, I. O. (2021). Alat penyortir buah tomat berdasarkan warna berbasis mikrokontroller Arduino. Jurnal Penelitian Inovatif, 1(2), 119–130. https://doi.org/10.54082/jupin.18
Ibnutama, K., Suryanata, M. G., Putri, R. O., & Al Hafiz, A. (2023). Seleksi tingkat kematangan citra buah belimbing menggunakan ruang warna CMYK. Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer), 22(2), 302–310.
Imaduddin, A. H., & Susanto, W. H. (2017). Pengaruh tingkat kematangan buah belimbing (Averrhoa carambola L.) dan proporsi penambahan gula terhadap karakteristik fisikokimia dan organoleptik lempok belimbing. Jurnal Pangan dan Agroindustri, 5(2). https://repository.ub.ac.id/id/eprint/151451/
Laili, N., Supriyanto, S., & Saraswati, M. (2023). Uji aktivitas ekstrak daun belimbing manis (Averrhoa carambola L.) terhadap penyembuhan luka sayat pada kelinci New Zealand. Jurnal Sains dan Kesehatan, 5(5), 731–739. https://doi.org/10.30872/jsk.v5i5.585
Maliki, M. S. A., & Irawan, D. (2024). Penyortiran kematangan buah dengan indikator warna menggunakan metode backpropagation berbasis IoT. Smart Comp: Jurnalnya Orang Pintar Komputer, 13(2), 341–348. https://doi.org/10.30591/smartcomp.v13i2.6415
Mampeu, C. Z., Agbo, A. E., Desfontis, J.-C., & Soro, D. (2024). Impact of season and maturity stage on biochemical parameters of Averrhoa carambola fruits. World Journal of Advanced Research and Reviews, 24(1), 1862–1870. https://doi.org/10.30574/wjarr.2024.24.1.3153
Sani, R. A., & Maha, A. I. (2018). Konstruksi timbangan digital menggunakan load cell berbasis Arduino Uno dengan tampilan LCD (liquid crystal display). Einstein E-Journal, 5(2), 16-19. https://doi.org/10.24114/einstein.v5i2.11837
Setiawan, M. D. C., Farida, I. N., & Niswatin, R. K. (2020). Klasifikasi mutu buah belimbing (Averrhoa carambola L.) menggunakan metode GLCM (gray level co-occurrence matrix). Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), 4(1), 93–100. https://doi.org/10.29407/inotek.v4i1.179
Sundari, S., Siburian, I. N., & Wulan, N. (2023). Mendeteksi tingkat kematangan belimbing berdasarkan fitur warna menggunakan transformasi ruang warna HSI. Algoritma: Jurnal Ilmu Komputer dan Informatika, 7(1). https://doi.org/10.30829/algoritma.v7i1.15263
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