DEVELOPMENT OF A WEB-BASED PURCHASE ORDER SYSTEM IN THE PURCHASING DIVISION USING THE AGILE MODEL (CASE STUDY: CV KLAMBY)
Article Sidebar
August 30, 2025
August 1, 2025
-
Agile, Approval, Information System, Purchase Order, Web-Based Application
Abstract
This study aims to design and develop a web-based purchase order (PO) system equipped with an integrated approval feature by implementing the Agile development methodology. Agile is chosen for its iterative, flexible, and user-oriented development approach. The research follows several stages, including planning, requirements analysis, system design, development, testing, implementation, and evaluation. The system was developed using JavaScript (Node.js) and MySQL, and tested through blackbox testing. The results show that the system effectively facilitates PO creation, vendor and product data management, and supports secure, automated multi-level approval. The implementation of this system has been proven to enhance the efficiency and accuracy of procurement processes, reduce human error, and provide better-organized documentation. This system is expected to serve as a digital solution that can be adopted by other companies and strengthen the application of Agile methodology in information system development projects.
Full text article
References
Alon, I., Sauge Berthelsen, A., Bjellerås, E., & Silva-Rêgo, B. (2025). Decentralized autonomous organizations: The new global digital venture capital. Research in International Business and Finance, 74, 102671. https://doi.org/10.1016/j.ribaf.2024.102671
Amraouy, O., Benbrahim, M., & Kabbaj, M. N. (2025). A blockchain- and self-sovereign identity-based collaborative framework for secure and verifiable cross-organizational data sharing in smart irrigation. Smart Agricultural Technology, 12, 101654. https://doi.org/10.1016/j.atech.2025.101654
Balakera, N., Tzelepi, V., Konstantinidis, F. K., Tsimiklis, G., & Amditis, A. (2024). Green ICT Methodology for Energy Consumption Calculation in ICT Architecture Components. 5th International Conference on Industry 4.0 and Smart Manufacturing (ISM 2023), 232, 1944–1952. https://doi.org/10.1016/j.procs.2024.02.016
Bründl, P., Wegener, C., Stoidner, M., Bayer, J., Scheffler, B., Nguyen, H. G., & Franke, J. (2025). Designing worker assistance systems–Methodology development and industrial validation. Journal of Manufacturing Systems, 80, 272–293. https://doi.org/10.1016/j.jmsy.2025.02.022
Capozza, M., Mangia, A., Gagliardi, M., Stefania, R., Garello, F., Conti, L., & Terreno, E. (2025). In situ sonoporation to enhance the tumour uptake of silicon phthalocyanine and improve PDT effectiveness in a triple negative breast cancer murine model. Journal of Photochemistry and Photobiology B: Biology, 272, 113266. https://doi.org/10.1016/j.jphotobiol.2025.113266
Castillo, C., Viu-Roig, M., Alvarez-Palau, E. J., & Gottardello, D. (2024). Foodtech in motion: Innovation and digitalisation of the food service sector in the post-pandemic Spain. British Food Journal, 126(12), 4182–4211. https://doi.org/10.1108/BFJ-10-2023-0943
Chavez, E., Williams, B. A., Beitelshees, M., Gorecki, G., & True, J. M. (2025). Enhancing pandemic preparedness through effective national policies: A global perspective. Drug Discovery Today, 30(12), 104506. https://doi.org/10.1016/j.drudis.2025.104506
Duan, X., Chen, J., Jiang, S., Qing, L., He, X., He, J., Lei, Y., Shi, H., Song, T., Jiao, X., Li, G., Huang, H., Guo, M., Gu, Y., Zhao, C., Yin, X., Liu, S., Wang, P., & Song, X. (2025). A novel machine learning framework-based rapid screening of ionizable lipids in LNPs for highly-efficient mRNA expression. Acta Pharmaceutica Sinica B. https://doi.org/10.1016/j.apsb.2025.10.040
Ganesan, V., Rahul, B., Anjana Devi, V., Viriyala, S. A. P., Govindaraj, R., Chowdhury, S., & Lin, J. C.-W. (2024). Chapter 8—Blockchain-based smart supply chain and transportation for Agri 4.0. In S. Kadry, V. Sharma, R. K. Dhanaraj, R. H. Jhaveri, & G. Vendhan (Eds.), Agri 4.0 and the Future of Cyber-Physical Agricultural Systems (pp. 135–156). Academic Press. https://doi.org/10.1016/B978-0-443-13185-1.00008-3
Garay Gallastegui, L. M., & Reier Forradellas, R. (2024). FASECO: A Framework for Advanced Support of E-Commerce and digital transformation in SMEs with natural language processing-enhanced analysis. Journal of Open Innovation: Technology, Market, and Complexity, 10(4), 100412. https://doi.org/10.1016/j.joitmc.2024.100412
Govindan, K., Jain, P., Kr. Singh, R., & Mishra, R. (2024). Blockchain technology as a strategic weapon to bring procurement 4.0 truly alive: Literature review and future research agenda. Transportation Research Part E: Logistics and Transportation Review, 181, 103352. https://doi.org/10.1016/j.tre.2023.103352
Henkel, D. A., & Ivens, B. S. (2025). Conceptualizing the Industrial Metaverse: From Technological Layers to Business Value. Industrial Marketing Management, 131, 58–72. https://doi.org/10.1016/j.indmarman.2025.10.003
Huang, S., Algarín, J. M., Alonso, J., Anieyrudh, R., Borreguero, J., Bschorr, F., Cassidy, P., Choo, W. M., Corcos, D., Guallart-Naval, T., Han, H. J., Igwe, K. C., Kang, J., Li, J., Littin, S., Liu, J., Rodriguez, G. G., Solomon, E., Tan, L.-K., … Blümich, B. (2025). Experience of how to build an MRI machine from scratch. Progress in Nuclear Magnetic Resonance Spectroscopy, 150–151, 101574. https://doi.org/10.1016/j.pnmrs.2025.101574
Hutton, S., Demir, R., & Eldridge, S. (2024). A microfoundational view of the interplay between open innovation and a firm’s strategic agility. Long Range Planning, 57(3), 102429. https://doi.org/10.1016/j.lrp.2024.102429
Javaid, M., & Haleem, A. (2025). Chapter 11—Role of digital twin and blockchain in logistics and supply chain management. In T. A. Nguyen (Ed.), Digital Twin and Blockchain for Sensor Networks in Smart Cities (pp. 243–264). Elsevier. https://doi.org/10.1016/B978-0-443-30076-9.00012-1
Kadri, S., Craven, K. E., Fussell, A. M., Gee, E. P. S., Jordan, D., Klee, E. W., Krumm, N., Temple-Smolkin, R. L., Zehir, A., Zhang, W., & Sboner, A. (2025). Clinical Bioinformatician Body of Knowledge—Bioinformatics and Software Core: A Report of the Association for Molecular Pathology. The Journal of Molecular Diagnostics, 27(7), 566–582. https://doi.org/10.1016/j.jmoldx.2025.04.008
Kang, P. S., Enstroem, R., Bhawna, B., & Bennett, O. (2025). A text mining study of competencies in modern supply chain management with skillset mapping. Supply Chain Analytics, 10, 100117. https://doi.org/10.1016/j.sca.2025.100117
Khan, MD. A., Rahman, A., Mahmud, F. U., Bishnu, K. K., Ahmed, M., Mridha, M. F., & Aung, Z. (2025). A systematic review of AI-driven business models for advancing Sustainable Development Goals. Array, 28, 100539. https://doi.org/10.1016/j.array.2025.100539
Longato, D., Cortinovis, C., Balzan, M., & Geneletti, D. (2024). Identifying suitable policy instruments to promote nature-based solutions in urban plans. Cities, 154, 105348. https://doi.org/10.1016/j.cities.2024.105348
Matekaire, K., & Siriram, R. (2025). An overview of factors influencing the adoption of IoT payment systems in South Africa’s small and medium-sized retail enterprises. Journal of Open Innovation: Technology, Market, and Complexity, 11(3), 100566. https://doi.org/10.1016/j.joitmc.2025.100566
Monteiro, T., Abrantes, S., & Ratinho, M. (2024). A Solution for Submitting Expenses. International Conference on Industry Sciences and Computer Science Innovation, 237, 20–27. https://doi.org/10.1016/j.procs.2024.05.075
Mukhopadhyay, S., Singh, R. K., & Jain, T. (2024). Developing artificial intelligence enabled Marketing 4.0 framework: An Industry 4.0 perspective. Qualitative Market Research: An International Journal, 27(5), 841–865. https://doi.org/10.1108/QMR-06-2023-0086
Nabli, H., Ghannem, A., Djemaa, R. B., & Sliman, L. (2025). How innovative technologies shape the future of pharmaceutical supply chains. Computers & Industrial Engineering, 199, 110745. https://doi.org/10.1016/j.cie.2024.110745
Palvia, P., Ghosh, J., Jacks, T., & Serenko, A. (2024). Global perspectives on organizational information systems issues: An enigma in search of a theoretical framework. Information & Management, 61(8), 10k4034. https://doi.org/10.1016/j.im.2024.104034
Puthenveettil, N. R., & Sappati, P. K. (2024). A review of smart contract adoption in agriculture and food industry. Computers and Electronics in Agriculture, 223, 109061. https://doi.org/10.1016/j.compag.2024.109061
Singh, N., Awan, U., Basahel, S., & Alghafes, R. (2025). Digital technology adoption and SC recoverability. The mediating role of relationship transparency and SC production risk management capabilities. Technological Forecasting and Social Change, 218, 124219. https://doi.org/10.1016/j.techfore.2025.124219
Spreitzenbarth, J. M., Bode, C., & Stuckenschmidt, H. (2024). Artificial intelligence and machine learning in purchasing and supply management: A mixed-methods review of the state-of-the-art in literature and practice. Journal of Purchasing and Supply Management, 30(1), 100896. https://doi.org/10.1016/j.pursup.2024.100896
Su, Y.-S., Wang, J., Tu, S.-H., Liao, K.-T., & Lin, C.-L. (2025). Detecting latent topics and trends in IoT and e-commerce using BERTopic modeling. Internet of Things, 32, 101604. https://doi.org/10.1016/j.iot.2025.101604
Vaidh, D., Bang, S., & Tripathy, B. K. (2025). Chapter 9—Blockchain-based supply chain management for smart disaster relief. In A. K. Das, D. Sinha, S. Bhattacharyya, & D. De (Eds.), The Role of Blockchain in Disaster Management (pp. 171–192). Academic Press. https://doi.org/10.1016/B978-0-443-13472-2.00015-2
Zhao, L., & Zhang, J. (2024). Machine learning based business intelligence security and privacy analysis with gaming model in training complexity application. Entertainment Computing, 50, 100695. https://doi.org/10.1016/j.entcom.2024.100695
Authors
Copyright (c) 2025 Fauziah Ika Mawarni, Fahrul Razi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.