Palembang Tie-Dye Fabric Motif Detection Software Using The Yolov10 Method
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Abstract
Palembang's jumputan cloth shops face difficulties in manually identifying motifs, which can lead to inventory errors. This study aims to develop a jumputan cloth motif detection software using YOLOv10 for real-time inventory identification and management automation on Android. The research method combines Research and Development (R&D) with an experimental quantitative approach. The population consists of fabric stocks from three Palembang shops, a sample of 400 images (Titik Tujuh, Beras Tabur, Lereng, Keong) divided into training (80%), validation (10%), and testing (10%). Instruments include a smartphone camera, YOLOv10m, and Google Colab Pro; analysis uses precision, recall, mAP50-95, and confusion matrix. The results show mAP50-95 up to 99.50%, smartphone accuracy 90-100% (SGD is superior), user satisfaction 96.52% via USE Questionnaire, but decreases in low light (Keong 40%). Conclusion: The application effectively supports business efficiency and cultural preservation with a detection time of 3-5 seconds.
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References
Agustini, M., & Syarifudin, A. (2024). Penggunaan media Instagram dalam mempertahankan budaya lokal kain jumputan Kota Palembang (@bebajoemputan). Pubmedia Social Sciences and Humanities, 1(3), 12. https://doi.org/xxxx
Bakar, A., & Halim, B. (2023). Komunikasi visual penjenamaan dalam upaya membangun citra visual identitas baru Kota Palembang. Besaung: Jurnal Seni Desain dan Budaya, 8(2), 151–161. https://doi.org/xxxx
Creswell, J. W., & Creswell, J. D. (2021). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications.
Emzir. (2021). Metodologi penelitian kualitatif: Kuantitatif. Pustaka Setia.
Guan, S., Lin, Y., Lin, G., Su, P., Huang, S., Meng, X., Liu, P., & Yan, J. (2024). Real-time detection and counting of wheat spikes based on improved YOLOv10. Agronomy, 14(9), Article 1936. https://doi.org/10.3390/agronomy14091936
Kar, S., & El-Sharkawi, M. (2023). Object detection using vision transformed EfficientDet. NAECON 2023 - IEEE National Aerospace and Electronics Conference, 214–220. https://doi.org/10.1109/NAECON57162.2023.10213000
Nainggolan, E. R., & Susafa’ati, S. (2018). Rancang bangun sistem informasi pelayanan rukun warga pada rusunawa Pesakih Jakarta Barat. Seminar Nasional Ilmu Terapan, 2(1), C04-1–C04-6.
Nazir, T., Nawaz, M., Rashid, J., Mahum, R., Masood, M., Mehmood, A., Ali, F., Kim, J., Kwon, H.-Y., & Hussain, A. (2021). Detection of diabetic eye disease from retinal images using a deep learning based CenterNet model. Sensors, 21(16), Article 5283. https://doi.org/10.3390/s21165283
Oktovianny, L. (2021). Kajian etnolingusitik dan leksikon kain tradisional masyarakat Palembang. Prosiding Seminar Nasional Linguistik dan Sastra (SEMANTIKS), 3, 716–720.
Rini Murbaningsih. (2023, May 29). Jumputan Palembang. Kementerian Keuangan Republik Indonesia. https://www.kemenkeu.go.id/jumputan-palembang
Sugiyono. (2023). Metode penelitian kuantitatif, kualitatif, R&D, dan kombinasi (mixed) (3rd ed.). Alfabeta.
Suhel, S., Melliny, V. D., Nailis, W., Darmawahyuni, A., Yuniarti, E., & Gustriani, G. (2023). Pemberdayaan perempuan Desa Ulak Kembahang II untuk meningkatkan pendapatan keluarga melalui pelatihan pembuatan batik jumputan Palembang. Sricommerce: Journal of Sriwijaya Community Services, 4(1), 39–48. https://doi.org/10.37388/sricommerce.v4i1.456
Sudaryono. (2022). Metodologi penelitian pendidikan. Rineka Cipta.
Syahputra, Z. (2023). Penerapan SSD-MobileNet dalam identitas jenis buah apel. Indonesian Journal of Education and Computer Science, 1(1), 1–7. https://doi.org/xxxx
Wahyuni, S., & Riyadi, S. (2020). Teknologi tepat guna UMKM Kotim simulasi harga komputer rakitan menggunakan sistem pendukung keputusan. Journal of Computer System and Informatics (JoSYC), 1(4), 358–366. https://doi.org/10.30865/josyc.v1i4.1234