Sistem Pendeteksi Tingkat Kesegaran Daging Ayam pada Citra Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Android
DOI:
https://doi.org/10.46880/jmika.Vol8No2.pp301-312Keywords:
CNN, Detection, Freshness, Chicken, ApplicationAbstract
This research develops a chicken meat freshness detection system based on image processing, implemented on an Android platform using the Convolutional Neural Network (CNN) method optimized with TensorFlow Lite. The system classifies chicken meat into three categories: fresh, less fresh, and rotten. The CNN model uses 32 filters to enhance feature extraction from the meat images. Testing on 30 samples, with each category tested 10 times, showed an accuracy of 90%, with 27 correct detections and 3 errors in the less fresh category. While the system effectively identifies fresh and rotten categories, there is a challenge in distinguishing the less fresh category due to its ambiguous visual characteristics. One limitation is the lack of a bounding box, causing the application to still provide detection results even when the scanned object is not chicken meat. This application is specifically designed to detect chicken meat pieces, so it is not recommended for use outside this context.
References
Abiyasa, R. A., & Romadhon, R. H. (2023). Implementasi Pengolahan Citra HSV Secara Real Time Sebagai Klasifikasi Tingkat Kesegaran Daging Ayam Potong Dengan Metode KNN. Seminar Nasional Teknologi Industri, 1(1), 1001–1010.
Agung Mujiono, A., Kartini, K., & Yulia Puspaningrum, E. (2024). IMPLEMENTASI MODEL HYBRID CNN-SVM PADA KLASIFIKASI KONDISI KESEGARAN DAGING AYAM. JATI (Jurnal Mahasiswa Teknik Informatika), 8(1), 756–763. https://doi.org/10.36040/jati.v8i1.8855
Agus Setiadi, Titik Ekowati, K. A. (2020). Analisis Preferensi Konsumen Dalam Membeli Daging Ayam Broiler Di Pasar Tradisional Kota Semarang, Jawa Tengah. AGROMEDIA: Berkala Ilmiah Ilmu-Ilmu Pertanian, 38(2), 76–89. https://doi.org/10.47728/ag.v38i2.287
Cakra, C., Syarif, S., Gani, H., & Patombongi, A. (2022). ANALISIS KESEGARAN IKAN MUJAIR DAN IKAN NILA DENGAN METODE CONVOLUTIONAL NEURAL NETWORK. Simtek : Jurnal Sistem Informasi Dan Teknik Komputer, 7(2), 74–79. https://doi.org/10.51876/simtek.v7i2.138
Dijaya, R. (2023). Buku Ajar Pengolahan Citra Digital. In Umsida Press. Umsida Press. https://doi.org/10.21070/2023/978-623-464-075-5
Hakim, A. A. (2021). Klasifikasi Human Activity Recognition Menggunakan Metode CNN. Jurnal Repositor, 3(2). https://doi.org/10.22219/repositor.v3i2.1265
Herianto, Adam Arif Budiman, Linda Nur Afifa, Timor Setiyaningsih, & Tri Amin Ridho. (2023). Membangun Model Pengidentifikasi Kesegaran Daging dengan Metode Jaringan Syaraf Konvolusi (CNN) Jenis Resnet-50. IKRA-ITH Informatika : Jurnal Komputer Dan Informatika, 7(3), 113–119. https://doi.org/10.37817/ikraith-informatika.v7i3.3072
Imanudin, R. F. N., Kustiawan, I., & Elvyanti, S. (2023). Steganografi Citra Digital Menggunakan Pendekatan Least Significant Bit dan Discrete Cosine Transform. Seminar Nasional Teknik Elektro.
Kholik, A. (2021). Klasifikasi Menggunakan Convolutional Neural Network (CNN) Pada Tangkapan Layar Instagram. Jurnal Data Mining Dan Sistem Informasi, 2(2), 10. https://doi.org/10.33365/jdmsi.v2i2.1345
Laia, M., Hondro, R. K., & Zebua, T. (2021). Implementasi Pengolahan Citra dengan Menggunakan Metode K-Nearest Neighbor Untuk Mengetahui Daging Ayam Busuk dan Daging Ayam Segar. JURIKOM (Jurnal Riset Komputer), 8(2), 39–49. https://doi.org/http://dx.doi.org/10.30865/jurikom.v8i2.2818
Prastowo, E. Y. (2021). Pengenalan Jenis Kayu Berdasarkan Citra Makroskopik Menggunakan Metode Convolutional Neural Network. Jurnal Teknik Informatika Dan Sistem Informasi, 7(2), 489–497. https://doi.org/10.28932/jutisi.v7i2.3706
Susim, T., & Darujati, C. (2021). Pengolahan Citra untuk Pengenalan Wajah (Face Recognition) Menggunakan OpenCV. Jurnal Syntax Admiration, 2(3), 534–545. https://doi.org/10.46799/jsa.v2i3.202
Wulandari, I., Yasin, H., & Widiharih, T. (2020). Klasifikasi Citra Digital Bumbu dan Rempah Dengan Algoritma Convolutional Neural Network (CNN). Jurnal Gaussian, 9(3), 273–282. https://doi.org/10.14710/j.gauss.v9i3.27416
Yulianto, A., Andreas, W., & Sabariman, S. (2023). Perancangan Prototype Brankas Menggunakan Sistem Pengenalan Wajah Dengan Metode Convolutional Neural Network (CNN). Telcomatics, 8(1), 10. https://doi.org/10.37253/telcomatics.v8i1.7852
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Rayhan Naturizal, Wahyu Fuadi, Lidya Rosnita
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
