DOI of the published article https://doi.org/10.31937/sk.v16i2.3869
Development of Cavendish Banana Maturity Detection and Sorting System Using Open Source Computer Vision and Loadcell Sensor
Pengembangan Sistem Pendeteksi Kematangan dan Penyortiran Pisang Cavendish Menggunakan Open Source Computer Vision dan Sensor Loadcell
DOI:
https://doi.org/10.21070/ups.7182Keywords:
Banana Maturity Detector, Sortation, OpenCV, Loadcell Sensor, ArduinoAbstract
This research aims to develop a system for detecting the maturity and sorting of Cavendish bananas using OpenCV and a load cell sensor. Current manual sorting is inefficient and inaccurate due to human sensitivity to lighting changes and fatigue. The system uses a webcam for image processing and a load cell for weight measurement, controlled by an Arduino Uno microcontroller. The HSV algorithm determines banana ripeness based on skin color. Test results show an average weight error of 0.08% for ripe bananas and 0.71% for unripe ones, while color detection achieves 47.34% accuracy in bright lighting. The system improves sorting efficiency with adequate accuracy, but further development is needed to enhance accuracy levels.
Downloads
References
B. S. Purwokol and K. Suryana, “Efek Suhu Simpan dan Pelapis terhadap Perubahan Kualitas Buah Pisang Cavendish,” Bul. Agron, vol. 28, no. 3, pp. 77–84, 2020.
R. Arifuddin, S. Subairi, A. B. Setiawan, M. A. Ridlo, and A. N. Ziliwu, “Determining PID Parameters For Temperature Control System in Cavendish Banana Storage Room,” JEEE-U (Journal Electr. Electron. Eng., vol. 8, no. 1, pp. 15–23, 2024, doi: 10.21070/jeeeu.v8i1.1683.
A. L. Baihaqi, T. P. Fiqar, and B. M. Pratama, “Klasifikasi Kematangan Musa Paradisiaca L Berbasis Warna Kulit Menggunakan Metode Decision Tree,” J. Borneo Inform. dan Tek. Komput., vol. 3, no. 2, pp. 14–22, 2023, doi: 10.35334/jbit.v3i2.3317.
M. F. Ajizi, D. Syauqy, M. Hannats, and H. Ichsan, “Klasifikasi Kematangan Buah Pisang Berbasis Sensor Warna Dan Sensor Load Cell Menggunakan Metode Naive Bayes,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 3, no. 3, pp. 2472–2479, 2019, [Online]. Available: https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/4692
M. Z. Andrekha and Y. Huda, “Deteksi Warna Manggis Menggunakan Pengolahan Citra dengan Opencv Python P - ISSN : 2302-3295,” vol. 9, no. 4, 2021.
H. Muchtar and R. Apriadi, “Implementasi Pengenalan Wajah Pada Sistem Penguncian Rumah Dengan Metode Template Matching Menggunakan Open Source Computer Vision Library (Opencv),” Resist. (elektRonika kEndali Telekomun. tenaga List. kOmputeR), vol. 2, no. 1, p. 39, 2019, doi: 10.24853/resistor.2.1.39-42.
M. Faisal, F. Albogamy, H. Elgibreen, M. Algabri, and F. A. Alqershi, “Deep Learning and Computer Vision for Estimating Date Fruits Type, Maturity Level, and Weight,” IEEE Access, vol. 8, no. Figure 1, pp. 206770–206782, 2020, doi: 10.1109/ACCESS.2020.3037948.
I. Anshory, I. Robandi, and M. Ohki, “System Identification of BLDC Motor and Optimization Speed Control Using Artificial Intelligent,” Int. J. Civ. Eng. Technol., vol. 10, no. 7, pp. 1–13, 2019, [Online]. Available: http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=10&IType=7http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10&IType=7
A. Roihan, P. A. Sunarya, and A. S. Rafika, “Pemanfaatan Machine Learning dalam Berbagai Bidang: Review paper,” IJCIT (Indonesian J. Comput. Inf. Technol., vol. 5, no. 1, pp. 75–82, 2020, doi: 10.31294/ijcit.v5i1.7951.
Y. Amrozi, D. Yuliati, A. Susilo, N. Novianto, and R. Ramadhan, “Klasifikasi Jenis Buah Pisang Berdasarkan Citra Warna dengan Metode SVM,” J. Sisfokom (Sistem Inf. dan Komputer), vol. 11, no. 3, pp. 394–399, 2022, doi: 10.32736/sisfokom.v11i3.1502.
Waryat and Nurjanani, “Efektivitas Bimbingan Teknis Budidaya Dan Pengolahan Pisang Terhadap Peningkatan Pengetahuan Dan Respon Petani Di Kabupaten Gowa Dan Takalar, Sulawesi Selatan,” Pros. Semin. Nas. Has. Penelit. Agribisnis VI, no. 1, pp. 447–452, 2022, [Online]. Available: https://jurnal.unigal.ac.id/index.php/prosiding/article/view/7766%0Ahttps://jurnal.unigal.ac.id/index.php/prosiding/article/download/7766/4909
R. Isum, S. Maryati, and B. Tryatmojo, “Raden Isum Suryani Maryati Akurasi Sistem Face Recognition Akurasi Sistem Face Recognition OpenCV Menggunakan Raspberry Pi Dengan Metode Haar Cascade KATA KUNCI Akurasi Face Recognition Raspberry Pi OpenCV Haar Cascade,” J. Ilm. Inform., no. Cv, p. 12790, 2019.
I. Sulistiyowati and M. I. Muhyiddin, “Disinfectant Spraying Robot to Prevent the Transmission of the Covid-19 Virus Based on the Internet of Things (IoT),” J. Electr. Technol. UMY, vol. 5, no. 2, pp. 61–67, 2021, doi: 10.18196/jet.v5i2.12363.
Jamaaluddin, A. Akbar, and Khoiri, “Ultrasonic Flow Meters and Microcontrollers for Precise Water Management with 6.45% Error Margin,” IOP Conf. Ser. Earth Environ. Sci., vol. 1242, no. 1, 2023, doi: 10.1088/1755-1315/1242/1/012017.
A. Ahfas, M. B. Ulum, D. H. R. Saputra, and S. Syahrorini, “Automatic Spray Desinfectant Chicken with Android Based on Arduino Uno,” IOP Conf. Ser. Earth Environ. Sci., vol. 519, no. 1, 2020, doi: 10.1088/1755-1315/519/1/012013.
M. F. Laksono Hadi, I. Sulistiyowati, J. Jamaaluddin, and I. Anshory, “Design of a Height and Weight Measurement Tool for Toddlers at Spreadsheet-Based Posyandu,” JEEE-U (Journal Electr. Electron. Eng., vol. 7, no. 2, pp. 163–175, 2023, doi: 10.21070/jeeeu.v7i2.1677.
A. Basrah Pulungan, Z. Nafis, M. Anwar, D. Elvanny Myori, and N. Padang, “Object Detection With a Webcam Using the Python Programming Language,” J. Appl. Eng. Technol. Sci., vol. 2, no. 2, pp. 103–111, 2023.
I. Sulistiyowati, H. M. Ichsan, and I. Anshory, “Konveyor Penyortir Objek Dengan Deteksi Warna Menggunakan Kamera Esp-32,” vol. 4, no. 1, 2024.
F. E. Saputra, R. Cahya Wihandika, and A. W. Widodo, “Penentuan Kualitas Biji Kopi Menggunakan Local Ternary Patterns Dan RGB-HSV Color Moment Dengan Learning Vector Quantization,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 5, no. 6, pp. 2299–2307, 2021, [Online]. Available: http://j-ptiik.ub.ac.id
D. S. Febriyan and R. D. Puriyanto, “Implementation of DC Motor PID Control on Conveyor for Separating Potato Seeds by Weight,” Int. J. Robot. Control Syst., vol. 1, no. 1, pp. 15–26, 2021, doi: 10.31763/ijrcs.v1i1.221.
Downloads
Additional Files
Posted
License
Copyright (c) 2025 UMSIDA Preprints Server
This work is licensed under a Creative Commons Attribution 4.0 International License.
