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Classification of Electrical Distribution Materials Based on Weight and Volume for Warehouse and Transportation Capacity Planning Achmad Freddya Eka Prasandha; Adithya Sudiarno; Rizki Revianto Putera
ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK Vol. 16 No. 2 (2026): ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK (July-November 2026 Edition)
Publisher : Universitas Panca Marga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51747/energy.v16i2.p361-373

Abstract

Electricity distribution logistics involves highly heterogeneous materials with different physical characteristics, creating challenges for warehouse capacity and transportation planning. Conventional material classification approaches mainly focus on economic value, demand frequency, or criticality, while physical logistics burdens generated by material weight and volume remain insufficiently represented. This study develops a weight–volume-based classification framework for electricity distribution materials to support physical logistics planning. A quantitative descriptive approach was applied using material master data and historical demand records from electricity distribution facilities in Central Java and the Special Region of Yogyakarta, Indonesia. Materials were classified into representative categories based on material characteristics, unit weight, and unit volume. Historical demand was then converted into total physical loads expressed in kilograms and cubic meters and aggregated by logistics location. The results identified 24 representative material categories with unit weights ranging from 0.50 to 3,300 kg and unit volumes from less than 0.01 to 4.40 m³. The highest physical demand was observed at UP3 Jogja, reaching 59.30 million kg and 120,221.83 m³. The findings demonstrate that material quantity alone is insufficient to represent logistics requirements in heterogeneous electricity distribution systems. The proposed weight–volume classification provides a practical basis for warehouse capacity evaluation, material handling planning, and transportation resource allocation.