Collaboration Design Between the Warehouse of Unit Pelaksana Pelayanan Pelanggan (UP3) and Unit Pelayanan Pelanggan (ULP) Using Agent-Based Modeling for Service Level Improvement and Cost Efficiency at PT PLN (Persero) Unit Induk Distribusi Jawa Barat

Authors

  • Ardiyan Wisnu Adi Faculty of Industrial Technology, Institut Teknologi Bandung
  • Rachmawati Wangsaputra Faculty of Industrial Technology, Institut Teknologi Bandung
  • Nur Faizatus Sa’idah Faculty of Industrial Technology, Institut Teknologi Bandung

Keywords:

Simulation, Collaboration, Agent-Based Modeling, Aplikasi Gudang Online, Warehouse Management System

Abstract

PT PLN (Persero) has implemented the Aplikasi Gudang Online (AGO) as part of its digital strategy to enhance warehouse management efficiency. Despite this, issues such as delayed material distribution, inventory mismatches, and data inaccuracy still persist. This study aims to evaluate and optimize the current warehouse system using an Agent-Based Modeling (ABM) approach via NetLogo. The model simulates interactions among producers, regional warehouses (UP3), and local warehouses (ULP) as agents within the distribution network for kWh Meter materials in the West Java region. Performance evaluation focuses on inventory levels, backlog quantities, and logistics cost efficiency. The outcome of this research is expected to produce a decision-support evaluation instrument for PT PLN (Persero), enabling more effective management of digital warehouse systems. Additionally, the study offers insights to improve real-time material distribution accuracy and system responsiveness, aligning with the corporation’s operational needs.

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References

Cahyanugraha, E. A., Isnanto, R., & Windasari, I. P. (2015). Desain dan Implementasi Sistem Online Gudang Pada PT.PLN (Persero) Distribusi Regional Jawa Tengah dan D.I Yogyakarta. Jurnal Teknologi Dan Sistem Komputer, Vol 3, No.1, 154–160. (Journal)

Zhu, W., 2015, Agent-Based Simulation and Modeling of Retail Center System, American Society of Civil Engineers, Vol. 142, 1-10. (Journal)

Macal, C. dan North, M., 2010, Tutorial on agent-based modelling and simulation, Journal of Simulation, Vol. 4, 151-162. (Journal)

Sopha, B. M., Sakti, S., Prasetia, A. C. G., Dwiansarinopa, M. W., & Cullinane, K. (2021). Simulating long-term performance of regional distribution centers in archipelagic logistics systems. Maritime Economics and Logistics, 23(4), 697–725. https://doi.org/10.1057/s41278-020-00166-3. (Journal)

Richards, & Gwynne. (2014). Warehouse Management: A Complete Guide to Improving Efficiency and Minimizing Costs in the Modern Warehouse 2nd Edition. (Book)

Zaman, S. I., Khan, S., Zaman, S. A. A., & Khan, S. A. (2023). A grey decision-making trial and evaluation laboratory model for digital warehouse management in supply chain networks. Decision Analytics Journal, 8. https://doi.org/10.1016/j.dajour.2023.100293. (Journal)

Avegliano, P., & Sichman, J. (2023). Equation-Based Versus Agent-Based Models: Why Not Embrace Both For an Efficient Parameter Calibration? JASSS, 26(4). https://doi.org/10.18564/jasss.5183. (Journal)

Daellenbach, H. G., & McNickle, D. C. (2005). Management Science: Decision-Making through Systems Thinking (2nd ed.). New York: Palgrave Macmillan. (Book)

Nagy, G., & Szentesi, S. (2024). Collaborative logistics: An innovative strategy to address future logistics challenges. Advanced Logistic Systems - Theory and Practice, 18(3), 83–95. https://doi.org/10.32971/als.2024.031 (Journal)

Teixeira, A. R., Ferreira, J. V., & Ramos, A. L., Optimization of Business Processes Through BPM Methodology: A Case Study on Data Analysis and Performance Improvement, Information, 15(11), pp. 724, Nov. 2024. (Journal)

Cimino, A., Filice, A.C., Longo, F., Mirabelli, G., Solina, V., Mallek-Daclin, S., Daclin, N., & Zacharewicz, G., Evolution of BPMN

and Simulation Integration: Trends, Challenges, and Future Directions, Procedia Computer Science, 253, pp. 3235–3246, 2025. (Journal)

Ning, L., & Yao, D., The Impact of Digital Transformation on Supply Chain Capabilities and Supply Chain Competitive Performance,

Sustainability, 15(13), pp. 10107, 2023. (Journal)

Fernando, Y., & Wulansari, P., Perceived Understanding of Supply Chain Integration, Communication and Teamwork Competency in the Global Manufacturing Companies, European Journal of Management and Business Economics, 30(2), pp. 191–210, May 2021. (Journal)

Khedr, A.M., & Sheeja Rani, S., Enhancing Supply Chain Management with Deep Learning and Machine Learning Techniques:

A Review, Journal of Open Innovation: Technology, Market, and Complexity, 10(4), pp. 100379, Dec. 2024. (Journal)

Davidsson, P., Henesey, L., Ramstedt, L., Törnquist, J., & Wernstedt, F. (2005). An analysis of agent-based approaches to transport

logistics, Transportation Research Part C: Emerging Technologies, 13(4), pp. 255–271. (Journal)

Parunak, H.V.D., Savit, R., & Riolo, R.L. (1998). Agent-based modeling vs. equation-based modeling: A case study and users’ guide.

Multi-agent systems and Agent-based Simulation. (Journal)

Railsback, S. F., & Grimm, V. (2012). Agent-based and individual-based modeling: A practical introduction. Princeton University Press. (Book).

Terzi, S., & Cavalieri, S. (2004). Simulation in the supply chain context: a survey. Computers in Industry, 53(1), 3–16. (Journal)

Longo, F., Nicoletti, L., & Padovano, A. (2019). Smart operators in industry 4.0: A human-centered approach to enhance operators’

capabilities and competencies within the new smart factory context. Computers & Industrial Engineering, 139, 105694. (Journal)

Epstein, J. M., & Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up. MIT Press.(Book)

S. F. Railsback and V. Grimm, Agent-Based and Individual-Based Modeling: A Practical Introduction, 2nd ed. Princeton, NJ: Princeton

University Press, 2019. (Book)

Published

2025-10-29

How to Cite

Adi, A. W., Wangsaputra, R., & Sa’idah, N. F. (2025). Collaboration Design Between the Warehouse of Unit Pelaksana Pelayanan Pelanggan (UP3) and Unit Pelayanan Pelanggan (ULP) Using Agent-Based Modeling for Service Level Improvement and Cost Efficiency at PT PLN (Persero) Unit Induk Distribusi Jawa Barat. ITB Graduate School Conference, 5(1). Retrieved from https://gcs.itb.ac.id/proceeding-igsc/index.php/igsc/article/view/707