Optimasi Strategi Supply Chain LPG Terminal Sekong dan Terminal Priok PT PP untuk Meningkatkan Efisiensi Operasional Penyaluran Bulk LPG di Wilayah Jawa Bagian Barat

Eri Wibowo; Timotius FCW Sutrisno; David Sukardi Kodrat; A.A.A Puty Andrina

doi:10.37034/jems.v8i1.268

Authors

Eri Wibowo Universitas Ciputra
Timotius FCW Sutrisno Universitas Ciputra
David Sukardi Kodrat Universitas Ciputra
A.A.A Puty Andrina Universitas Ciputra

DOI:

https://doi.org/10.37034/jems.v8i1.268

Keywords:

Terminal LPG, Optimasi Distribusi, Total Biaya, Heuristik, Linear Programming

Abstract

Penelitian ini mengkaji optimasi pola distribusi Liquefied Petroleum Gas (LPG) antara Terminal LPG (TLPG) Sekong dan TLPG Priok di wilayah Jawa bagian Barat untuk meningkatkan efisiensi biaya dan ketahanan stok. Pendekatan dua tahap digunakan. Tahap pertama menerapkan heuristik Evolutionary Algorithm (EA) pada Microsoft Excel Solver guna menghasilkan solusi awal pembagian suplai yang feasible dan biaya rendah. Tahap kedua menggunakan Linear Programming (LP) di Visual Studio Code (VS Code) bahasa Python dengan pustaka PuLP dan pandas untuk memperoleh solusi optimal secara matematis dan melakukan validasi hasil EA. Data operasional tahun 2024–2025 mencakup volume demand SPBE, jarak, tarif distribusi, dan kapasitas terminal. Hasil menunjukkan terjadi redistribusi suplai dari TLPG Priok ke TLPG Sekong yang meningkatkan ketahanan stok TLPG Priok (>4 hari) dan menurunkan total biaya distribusi dibanding kondisi eksisting. Model LP memberikan biaya sedikit lebih rendah dibanding EA, menegaskan komplementaritas kedua pendekatan. Temuan ini menyoroti pentingnya alokasi dinamis, koordinasi antar-terminal, dan dukungan sistem pengambilan keputusan berbasis data untuk menjaga security of supply dan efisiensi operasional.

References

Risnata, A. D., & Moeis, A. O. (2021). Developing KPI’s of Supply Chain LPG Using Analytic Hierarchy Process: a Case Study of LPG Scheduling at Indonesia’s LPG Main Terminal. Retrieved from https://easychair.org/publications/preprint/nJ6P

Cohen, M. A., & Mallik, S. (1997). Global Supply Chains: Research and Applications. Production and Operations Management, 6(3), 193–210. https://doi.org/10.1111/j.1937-5956.1997.tb00426.x

Santoso, T., Ahmed, S., Goetschalckx, M., & Shapiro, A. (2005). A stochastic programming approach for supply chain network design under uncertainty. European Journal of Operational Research, 167(1), 96–115. https://doi.org/10.1016/j.ejor.2004.01.046

Sharma, S., & Modgil, S. (2019). TQM, SCM and operational performance: an empirical study of Indian pharmaceutical industry. Business Process Management Journal, 26(1), 331–370. https://doi.org/10.1108/BPMJ-01-2018-0005

Ghobakhloo, M., & Azar, A. (2018). Business excellence via advanced manufacturing technology and lean-agile manufacturing. Journal of Manufacturing Technology Management, 29(1), 2–24. https://doi.org/10.1108/JMTM-03-2017-0049

Mogale, D. G., Ghadge, A., & Jena, S. K. (2025). Modelling and optimising a multi-depot vehicle routing problem for freight distribution in a retail logistics network. Computers & Industrial Engineering, 207, 111315. https://doi.org/10.1016/j.cie.2025.111315

Febry, T., & Widya Mandala, Y. (2015). Total Cost of Distribution Model Considering 4-echelon, Transportation Modes and Loading unloading Charges. In Proceding Seminar Nasional PPS-MTI UNPAR 2015. https://doi.org/10.13140/RG.2.1.2746.7605

Saraswati, R., Sutopo, W., & Hisjam, M. (2017). Penyelesaian Capacitated Vehicle Routing Problem dengan Menggunakan Algoritma Sweep untuk Penentuan Rute Distribusi Koran : Studi Kasus. Jurnal Manajemen Pemasaran, 11(2), 41–44. https://doi.org/10.9744/pemasaran.11.2.41-44

Hashi, E. K., Hasan, M. R., & Zaman, M. S. (2015). A heuristic solution of the Vehicle Routing Problem to optimize the office bus routing and scheduling using Clarke & Wright’s savings algorithm. 2015 International Conference on Computer and Information Engineering (ICCIE), 13–16. https://doi.org/10.1109/CCIE.2015.7399306

Talbi, E. (2009). Metaheuristics. John Wiley & Sons, Inc. https://doi.org/10.1002/9780470496916

Hiller, F., & Lieberman, G. (2005). Introduction to Operation Research (8th Edition). McGraw Hill.

Masudin, I. (2019). Location-Allocation Problems in the Perspective of Supply Chain: Approaches and Applications. Jurnal Teknik Industri, 20(1), 1–11. https://doi.org/10.22219/jtiumm.vol20.no1.1-11

Alkhawaldah, R. A., ALShalabi, F. S., Alshawabkeh, Z. A., Alsha’ar, H. Y., Alzoubi, M. Y., Alshawabkeh, R. O., & Dweiri, M. A. (2023). The mediating role of organizational capabilities on the relationship between lean supply chain and operational performance. Uncertain Supply Chain Management, 11(1), 11–20. https://doi.org/10.5267/j.uscm.2022.12.005

Garcia-Buendia, N., Moyano-Fuentes, J., Maqueira, J. M., & Avella, L. (2023). The lean supply chain management response to technology uncertainty: consequences for operational performance and competitiveness. Journal of Manufacturing Technology Management, 34(1), 67–86. https://doi.org/10.1108/JMTM-07-2022-0250

Laporte, G. (2009). Fifty Years of Vehicle Routing. Transportation Science, 43(4), 408–416. https://doi.org/10.1287/trsc.1090.0301

Trivedi, S. K., Roy, A. D., Kumar, P., Jena, D., & Sinha, A. (2024). Prediction of consumers refill frequency of LPG: A study using explainable machine learning. Heliyon, 10(1), e23466. https://doi.org/10.1016/j.heliyon.2023.e23466

Mavi, R. K., Mavi, N. K., Shekarabi, S. A. H., Pepper’s, M., & Arisian, S. (2023). Supply Chain Resilience: A Common Weights Efficiency Analysis with Non-discretionary and Non-controllable Inputs. Global Journal of Flexible Systems Management, 24(S1), 77–99. https://doi.org/10.1007/s40171-024-00380-5

Tian, M., Zhong, S., Al Ghassani, M. A., Johanning, L., & Sucala, V. I. (2024). Simulation and feasibility assessment of a green hydrogen supply chain: a case study in Oman. Environmental Science and Pollution Research, 32(22), 13313–13328. https://doi.org/10.1007/s11356-024-32563-z

Akbar, M. D., Rahman, A., & Mada Tantrika, C. F. (2013). Optimalisasi Aliran Distribusi dan Alokasi Material dengan Metode Linear Programming (Studi Kasus: PT. PLN (PERSERO) APJ Distribusi Malang). Jurnal Rekayasa dan Manajemen Sistem Industri, 1(2), 127990.

Eiben, A. E., & Smith, J. E. (2015). Introduction to Evolutionary Computing. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-44874-8