Retail Clustering Using K-Means to Optimize Intermediate Warehouse Locations for 3-kg LPG Distribution Based on Transportation Capacity

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Ryry Rizky Asri
Muhammad Nurman Helmi
Bram Andryanto
Ibnu Habib
Putri Zsa Zsa Leani Leuser
Putri Mety Zalynda
Yogi Yogaswara

Abstract

The distribution of 3-kg LPG in the Greater Bandung area faces efficiency challenges in facility placement and service area allocation. This study aims to determine intermediate warehouse locations using the K-Means Clustering method and to allocate demand based on vehicle capacity. The clustering process was conducted using customer location coordinates, individual customer demand, and available vehicle capacity. This method was used to group 72 agents into balanced clusters based on geographical proximity and vehicle capacity constraints, ensuring that each cluster can be served by one vehicle without exceeding its maximum capacity. Based on a total demand of 5,570 units and a vehicle capacity of 560 units, this study produced 10 clusters with an average demand of 557 units per cluster. The centroid of each cluster is proposed as a candidate location for an intermediate warehouse. The demand reallocation process resulted in a more balanced distribution, as indicated by a reduction in inter-cluster demand variance from 41.9 to 3. These results indicate that the integration of K-Means Clustering and capacity-based demand allocation can be used as an initial approach in designing a more balanced and structured 3-kg LPG distribution network.

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How to Cite
Asri, R. R., Helmi, M. N., Andryanto, B., Habib, I., Leuser, P. Z. Z. L., Zalynda, P. M., & Yogaswara, Y. (2026). Retail Clustering Using K-Means to Optimize Intermediate Warehouse Locations for 3-kg LPG Distribution Based on Transportation Capacity. Journal of Integrated System, 9(1), 33–47. https://doi.org/10.28932/jis.v9i1.13507
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References

Ahmed, M., Seraj, R. and Islam, S.M.S. (2020) ‘The k-means algorithm: a comprehensive survey and performance evaluation’, Electronics (Switzerland), 9(8), pp. 1–12. Available at: https://doi.org/10.3390/electronics9081295.

Alanasry, S.H. et al. (2024) ‘Analisis rute distribusi parfume di PT Maju Jaya menggunakan model milk run’, INNOVATIVE: Journal of Social Science Research, 4(4), pp. 8190–8198.

Aldi, A. (2025) Kecurangan distribusi gas LPG 3 kg rugikan negara hingga Rp13 triliun. Available at: https://insight.energika.id/amp/77961/kecurangan-distribusi-gas-lpg-3-kg-rugikan-negara-hingga-rp13-triliun.

Alfiyatin, A.N., Mahmudy, W.F. and Anggodo, Y.P. (2018) ‘K-means clustering and genetic algorithm to solve vehicle routing problem with time windows problem’, Indonesian Journal of Electrical Engineering and Computer Science, 11(2), pp. 462–468. Available at: https://doi.org/10.11591/ijeecs.v11.i2.pp462-468.

Arifin, M.Z. et al. (2021) ‘Konfigurasi jaringan supply chain pada distribusi gas LPG 3 kg di Indonesia’, Jurnal Ilmiah Teknik dan Manajemen Industri, 4(1). Available at: https://doi.org/10.32493/jitmi.v4i1.y2021.p1-9.

Boonyo, Y. (2025) ‘Thai text clustering with k-means and TF-IDF in Python for educational applications’, Journal of Research Methodology, 38(1).

Cheng, X. and Zheng, F. (2024) ‘Research on the application of weighted distance k-means clustering algorithm with capacity constraint in express service location’, in 2024 12th International Conference on Information Systems and Computing Technology (ISCTech), pp. 1–5. Available at: https://doi.org/10.1109/ISCTech63666.2024.10845541.

Chiang, T.A., Che, Z.H. and Hung, C.W. (2023) ‘A k-means clustering and the Prim’s minimum spanning tree-based optimal picking-list consolidation and assignment methodology for achieving the sustainable warehouse operations’, Sustainability (Switzerland), 15(4). Available at: https://doi.org/10.3390/su15043544.

Gaon, T., Gabay, Y. and Weiss Cohen, M. (2025) ‘Optimizing electric vehicle routing efficiency using k-means clustering and genetic algorithms’, Future Internet, 17(3). Available at: https://doi.org/10.3390/fi17030097.

Hidayatullah, N.A., Prihartono, W. and Rohman, F. (2025) ‘Clustering penerima bantuan pangan berbasis algoritma k-means untuk meningkatkan efektivitas program sosial di Kota/Kabupaten Cirebon’, Jurnal Informatika dan Teknik Elektro Terapan, 13(1). Available at: https://doi.org/10.23960/jitet.v13i1.5692.

Kronova, J. et al. (2024) ‘Application cluster analysis as a support form modelling and digitalizing the logistics processes in warehousing’, Applied Sciences (Switzerland), 14(11). Available at: https://doi.org/10.3390/app14114343.

Le, T.D.C. et al. (2022) ‘Clustering algorithm for a vehicle routing problem with time windows’, Transport, 37(1), pp. 17–27. Available at: https://doi.org/10.3846/transport.2022.16850.

Lestari, V., Azmi, N. and Arizky, S. (2022) Permasalahan dan tantangan transformasi kebijakan subsidi LPG 3 kilogram. Available at: https://repositori.dpr.go.id/id/eprint/263/

Masudin, I. (2016) Location-allocation modelling for Indonesian multi-echelon LPG supply chain. Available at: https://doi.org/10.25439/rmt.27581604.

Montolalu, G., Arie Mokorimban, M.T. and Sepang, M. (2024) ‘Penegakan hukum terhadap pelaku penyalahgunaan tabung liquefied petroleum gas 3 kg menurut Undang-Undang Nomor 22 Tahun 2001’, Lex Crimen, Jurnal Fakultas Hukum, UNSRAT, 12(5).

Nadhila, A.A., Ariyanto, Y. and Syaifudin, Y.W. (2024) ‘Clusterization of MSME and warehouse locations for efficiency of courier placement’, Journal of Evrímata: Engineering and Physics, pp. 144–149. Available at: https://doi.org/10.70822/journalofevrmata.v2i02.66.

Nurbani, S. (2019) ‘Rancangan distribusi LPG 3 kg berdasarkan kebijakan distribusi sistem tertutup di wilayah pemasaran Kota Bandung’, Jurnal Teknik Industri, 14(3), pp. 149–162. Available at: https://doi.org/10.14710/jati.14.3.149-162.

Oktaviani, P., Dalnis, I.P. and Wirdianto, E. (2025) ‘Usulan rute pendistribusian gas LPG menggunakan algoritma Djikstraa dan algoritma genetika pada model CGVRP’, Jurnal Rekayasa Sistem Industri, 14(1), pp. 131–145. Available at: https://doi.org/10.26593/jrsi.v14i1.8491.131-145.

Santoso, M. et al. (2024) ‘Penentuan rute distribusi LPG menggunakan teknik simulated annealing pada PT XYZ’, Jurnal Penelitian Rumpun Ilmu Teknik, 3(4), pp. 68–76. Available at: https://doi.org/10.55606/juprit.v3i4.4341.

Shukran, M.A.M. et al. (2022) ‘Survey on clustering techniques for image categorization dataset’, Journal of Computer and Communications, 10(06), pp. 177–185. Available at: https://doi.org/10.4236/jcc.2022.106014.

Siahaan, P., Chandra, T.Y. and Ismed, M. (2023) ‘Penegakan hukum terhadap pelaku tindak pidana penyalahgunaan gas LPG bersubsidi di DKI Jakarta’, Jurnal Global Ilmiah, 1(2), pp. 122–129.

Subakdo, W.A. and Nugroho, Y.A. (2016) ‘In-bound dan out-bound logistic pada distribusi LPG 3 kg di Indonesia’, in Prosiding Semnastek. Jakarta: Fakultas Teknik Univ. Muhammadiyah. Available at: jurnal.umj.ac.id/index.php/semnastek (Accessed: 23 July 2025).

Sunardhi, Y. et al. (2025) ‘Analisis kinerja jaringan distribusi LPG: studi kasus di Kecamatan Compreng’, Journal of Social Science Research, 5(1), pp. 2090–2106. Available at: https://doi.org/10.31004/innovative.v5i1.16819.

Tabianan, K., Velu, S. and Ravi, V. (2022) ‘K-means clustering approach for intelligent customer segmentation using customer purchase behavior data’, Sustainability (Switzerland), 14(12). Available at: https://doi.org/10.3390/su14127243.

Terlunen, S., Barreto, G. and Hellingrath, B. (2015) ‘Application and evaluation of multi-criteria clustering algorithms for customer-oriented supply chain segmentation’, in Conference: LM13 - Logistics Management. Springer Science and Business Media B.V., pp. 121–133. Available at: https://doi.org/10.1007/978-3-319-13177-1_10.

Utari, R.F. et al. (2024) ‘Pengelompokan data pendistribusian listrik menggunakan algoritma mean shift’, MALCOM: Indonesian Journal of Machine Learning and Computer Science, 4(3), pp. 1015–1023. Available at: https://doi.org/10.57152/malcom.v4i3.1428.

Villalba, A.F.L. and La Rotta, E.C.G. (2022) ‘Clustering and heuristics algorithm for the vehicle routing problem with time windows’, International Journal of Industrial Engineering Computations, 13(2), pp. 165–184. Available at: https://doi.org/10.5267/J.IJIEC.2021.12.002.

Xu, D. and Tian, Y. (2015) ‘A comprehensive survey of clustering algorithms’, Annals of Data Science, 2(2), pp. 165–193. Available at: https://doi.org/10.1007/s40745-015-0040-1.

Yin, R. and Lu, P. (2022) ‘A cluster-first route-second constructive heuristic method for emergency logistics scheduling in urban transport networks’, Sustainability (Switzerland), 14(4). Available at: https://doi.org/10.3390/su14042301.