NFT-Based Authentication of Lampung Tapis Cloth Using Hyperledger Fabric and ERP Odoo

Authors

  • Panji Andhika Pratomo✉ Department of Informatics Management, Politeknik Negeri Lampung, Bandar Lampung, Indonesia Author
  • Tri Sandhika Jaya Department of Informatics Management, Politeknik Negeri Lampung, Bandar Lampung, Indonesia Author
Diajukan 15 Okt 2024 Diterbitkan 31 Des 2024
DOI: https://doi.org/10.59025/f8d91baf

Keywords:

blockchain, Hyperledger Fabric, NFT, ERP Odoo, product authentication

Abstract

Tapis cloth of Lampung, a locally designated cultural heritage textile, faces persistent risks of counterfeiting and ownership-chain obfuscation, while paper-based authenticity mechanisms cannot provide auditable and transparent guarantees. This study designs and implements a blockchain-based authentication system that integrates Hyperledger Fabric 2.5 as the distributed ledger platform and ERP Odoo CE 16.0 as the production management layer, connected through a Node.js REST API middleware. The principal technical contribution is a Non-Fungible Token (NFT) issuance mechanism embedded in a Go chaincode that encapsulates SHA-256 hashes of each cloth metadata comprising the motif code, artisan identity, and timestamp thereby endowing every piece with a unique and unforgeable digital identity. Load testing with 200 concurrent transactions demonstrated system throughput of 120 transactions per second (TPS) at an average latency of 0.8 seconds, outperforming the conventional baseline by a factor of 2.67. QR-code-based authenticity verification achieved 100% accuracy across all test samples. The proposed system substantiates the feasibility of ERP–Blockchain integration as a transparent and trustworthy authentication infrastructure for micro-to-medium-scale craft industries.

References

  1. M. F. C. Perdana, V. Atina, dan F. E. Nastiti, "Sistem informasi pengelolaan magang berbasis web," INFORMASI (Jurnal Informatika dan Sistem Informasi), vol. 16, no. 2, hal. 231–243, 2024, doi: 10.37424/informasi.v16i2.314.
  2. E. Kurniawati dan A. Ikhwan, "Perancangan sistem informasi manajemen inventaris kontrol stok barang berbasis web," Jurnal Teknologi Sistem Informasi dan Aplikasi, vol. 6, no. 3, hal. 408–415, 2023, doi: 10.32493/jtsi.v6i3.30881.
  3. C. Januartika, R. Rosmiati, dan S. Sartana, "Analisis dan perancangan sistem informasi absensi berbasis web menggunakan QR code studi kasus: STMIK Palangkaraya," Jurnal Sistem Informasi, Manajemen dan Teknologi Informasi, vol. 1, no. 1, hal. 29–36, 2023, doi: 10.33020/jsimtek.v1i1.385.
  4. F. Stiehle dan I. Weber, "Blockchain for business process enactment: A taxonomy and systematic literature review," dalam Lecture Notes in Business Information Processing, vol. 460, Springer, 2022, hal. 5–20, doi: 10.1007/978-3-031-16168-1_1.
  5. O. Petto, T. Preindl, dan M. Kjäer, "Interpreted and confidential execution of process choreographies on a blockchain," dalam Lecture Notes in Business Information Processing, Springer, 2024, hal. 40–54, doi: 10.1007/978-3-031-70445-1_3.
  6. H. Taherdoost dan M. Madanchian, "Blockchain and business process management (BPM) synergy: A comparative analysis of modeling approaches," Information, vol. 15, no. 1, hal. 9, 2023, doi: 10.3390/info15010009.
  7. J. Gu, L. Zhao, X. Yue, N. I. Arshad, dan U. H. Mohamad, "Multistage quality control in manufacturing process using blockchain with machine learning technique," Inf. Process. Manag., vol. 60, no. 4, hal. 103341, 2023, doi: 10.1016/j.ipm.2023.103341.
  8. F. L. Gaol, M. F. Deniansyah, dan T. Matsuo, "The measurement impact of ERP system implementation on the automotive industry business process efficiency," Int. J. Business Information Systems, vol. 43, no. 3, hal. 429–442, 2023, doi: 10.1504/ijbis.2023.132124.
  9. S. Gandhi, A. Kiwelekar, L. Netak, dan S. Shahare, "A blockchain-based data-driven trustworthy approval process system," Int. J. Inf. Manag. Data Insights, vol. 3, no. 1, hal. 100162, 2023, doi: 10.1016/j.jjimei.2023.100162.
  10. T. Rahman et al., "Blockchain applications in business operations and supply chain management by machine learning," Int. J. Comput. Sci. Inf. Syst., no. 11, hal. 17–30, 2024, doi: 10.55640/ijcsis/volume09issue11-03.
  11. M. A. Al-Shboul, "Do artificial intelligence system adoptions foster production management supply chain performance in pharmaceutical manufacturing firms? An empirical exploring study from the MENA region," Bus. Process Manag. J., vol. 30, no. 7, hal. 2427–2455, 2024, doi: 10.1108/bpmj-02-2024-0089.
  12. W. Zhang, "Blockchain-based federated learning for device failure detection in industrial IoT," IEEE Internet Things J., vol. 8, no. 7, hal. 5926–5937, 2021, doi: 10.1109/JIOT.2020.3032544.
  13. H. Albayati, "Accepting financial transactions using blockchain technology and cryptocurrency: A customer perspective," Technol. Soc., vol. 62, hal. 101320, 2020, doi: 10.1016/j.techsoc.2020.101320.
  14. S. S. Kamble, "A machine learning based approach for predicting blockchain adoption in supply chain," Technol. Forecast. Soc. Change, vol. 163, hal. 120465, 2021, doi: 10.1016/j.techfore.2020.120465.
  15. G. Nuryyev et al., "Blockchain technology adoption behavior and sustainability of the business in tourism and hospitality," Sustainability, vol. 12, no. 3, hal. 1256, 2020, doi: 10.3390/su12031256.
  16. V. Chittipaka et al., "Blockchain technology for supply chains operating in emerging markets: An empirical examination of the TOE framework," Ann. Oper. Res., vol. 327, no. 1, hal. 465–492, 2023, doi: 10.1007/s10479-022-04801-5.
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How to Cite

NFT-Based Authentication of Lampung Tapis Cloth Using Hyperledger Fabric and ERP Odoo. (2024). Journal of Technology and Data Science, 2(2), 85-93. https://doi.org/10.59025/f8d91baf