IMPLEMENTASI ALGORITMA DEEP LEARNING YOLO (YOU ONLY LOOK ONCE) UNTUK DETEKSI KUALITAS KENTANG SEGAR DAN BUSUK SECARA REAL TIME
Abstract
Potatoes are one of the important sources of carbohydrates whose quality greatly affects the food industry. The potato quality inspection process that is still carried out manually is often time-consuming and prone to human error. This research developed a quality detection system for fresh and rotten potatoes using the YOLOv8n version of the You Only Look Once (YOLO) algorithm. The study began with the collection of 1000 potato photos that were split into 85% for training, 10% for validation, and 5% for testing. The dataset was then labeled using the Roboflow platform and was aggregated to bring the total to 2304 photos. The training results showed that the YOLOv8n model achieved 99.9% accuracy, 100% recall, 99.5% mAP50, and 97.9% mAP50-90. The model is implemented in a Flask-based website to enable real-time detection. Although the model produces good performance, there are some errors in recognizing object classes. Overall, this system is capable of effectively detecting the quality of potatoes, reducing waste, and maintaining product quality.
References
A. Fuadi And A. Suharso, “Perbandingan Arsitektur Mobilenet Dan Nasnetmobile Untuk Klasifikasi Penyakit Pada Citra Daun Kentang,” Jipi (Jurnal Ilm. Penelit. Dan Pembelajaran Inform., Vol. 7, No. 3, Pp. 701–710, 2022, Doi: 10.29100/Jipi.V7i3.3026.
I. S. Diva And S. Agmasari, “4 Cara Pilih Kentang Bagus, Jangan Pilih Yang Lembek.” [Online]. Available: Https://Www.Kompas.Com/Food/Read/2023/05/09/161000275/4-Cara-Pilih-Kentang-Bagus-Jangan-Pilih-Yang-Lembek
Z. S. Jannah And F. A. Sutanto, “Implementasi Algoritma Yolo ( You Only Look Once ) Untuk Deteksi Rias Adat Nusantara,” Vol. 22, No. 3, Pp. 1490–1495, 2022, Doi: 10.33087/Jiubj.V22i3.2421.
A. Wibowo, L. Lusiana, And T. K. Dewi, “Implementasi Algoritma Deep Learning You Only Look Once (Yolov5) Untuk Deteksi Buah Segar Dan Busuk,” Paspalum J. Ilm. Pertan., Vol. 11, No. 1, P. 123, 2023, Doi: 10.35138/Paspalum.V11i1.489.
S. N. Mashita, “Implementasi Deep Learning Object Detection Rambu K3 Pada Video Menggunakan Metode Convolutional Neural Network (Cnn) Dengan Tensorflow,” Skripsi, Stat. Fak. Mat. Dan Ilmu Pengetah. Alam, Univ. Islam Indones. Yogyakarta, Pp. I–89, 2020, [Online]. Available: Https://Dspace.Uii.Ac.Id/Bitstream/Handle/123456789/28781/16611128 Syinta Nuri Mashita.Pdf?Sequence=1&Isallowed=Y
P. R. Aningtiyas, A. Sumin, And S. Wirawan, “Pembuatan Aplikasi Deteksi Objek Menggunakan Tensorflow Object Detection Api Dengan Memanfaatkan Ssd Mobilenet V2 Sebagai Model Pra-Terlatih,” Vol. 19, No. September, Pp. 421–430, 2020, [Online]. Available: Https://Scholar.Archive.Org/Work/Itmgg3rr5fdh5armvk6ivykb2m/Access/Wayback/Https://Ejournal.Jak-Stik.Ac.Id/Index.Php/Komputasi/Article/Download/68/152
I. M. D. Maleh, R. Teguh, A. S. Sahay, S. Okta, And M. P. Pratama, “Implementasi Algoritma You Only Look Once (Yolo) Untuk Object Detection Sarang Orang Utan,” J. Inform., Vol. 10, No. 1, Pp. 19–27, 2023, Doi: 10.31294/Inf.V10i1.13922.
M. Sarosa And N. Muna, “Implementasi Algoritma You Only Look Once (Yolo) Untuk Deteksi Korban Bencana Alam,” J. Teknol. Inf. Dan Ilmu Komput., Vol. 8, No. 4, Pp. 787–792, 2021, Doi: 10.25126/Jtiik.202184407.
A. A. G. Bagus Janapriya, “Pengenalan Jenis Rambu Lalu Lintas Menggunakan Metode Yolo V5,” Jeliku (Jurnal Elektron. Ilmu Komput. Udayana), Vol. 11, No. 4, P. 1011, 2023, Doi: 10.24843/Jlk.2023.V11.I04.P32.
L. Rahma, H. Syaputra, A. H. Mirza, And S. D. Purnamasari, “Objek Deteksi Makanan Khas Palembang Menggunakan Algoritma Yolo (You Only Look Once),” J. Nas. Ilmu Komput., Vol. 2, No. 3, Pp. 213–232, 2021, Doi: 10.47747/Jurnalnik.V2i3.534.
T. Handayani, “Implementasi Metode You Only Look Once (Yolo) Untuk Deteksi Kesegaran Telur Ayam Berdasarkan Citra Cangkang,” Vol. 3, No. 0, Pp. 1–23, 2024, [Online]. Available: Https://Ejournal.Warunayama.Org/Index.Php/Kohesi/Article/View/4038
A. Harun, “Implementasi Deep Learning Menggunakan Metode Youonlylookonce Untuk Mendeteksi Rokok,” J. Ekon. Vol. 18, Nomor 1 Maret201, Vol. 2, No. 1, Pp. 41–49, 2023, [Online]. Available: Https://Repository.Uin-Suska.Ac.Id/65514/
L. Satya, M. R. D. S. Septian, M. W. Sarjono, M. Cahyanti, And E. R. Swedia, “Sistem Pendeteksi Plat Nomor Polisi Kendaraan Dengan Arsitektur Yolov8,” Sebatik, Vol. 27, No. 2, Pp. 753–761, 2023, Doi: 10.46984/Sebatik.V27i2.2374.
N. J. Hayati, D. Singasatia, And M. R. Muttaqin, “Object Tracking Menggunakan Algoritma You Only Look Once (Yolo)V8 Untuk Menghitung Kendaraan,” Komputa J. Ilm. Komput. Dan Inform., Vol. 12, No. 2, Pp. 91–99, 2023, Doi: 10.34010/Komputa.V12i2.10654.
M. Ibrahim And U. Latifa, “Penerapan Algoritma Yolov8 Dalam Deteksi Waktu Panen Tanaman Pakcoy Berbasis Website,” Jati (Jurnal Mhs. Tek. Inform., Vol. 7, No. 4, Pp. 2489–2495, 2024, Doi: 10.36040/Jati.V7i4.7154.
