Perencanaan Distribusi Berbasis DRP sebagai Strategi Efisiensi Biaya pada Industri Air Minum Dalam Kemasan (AMDK) - Saputra, Arie; Alfatah, Adrian (Universitas Teuku Umar, 2025)
This study aims to design an efficient distribution planning model for bottled drinking water (AMDK) products in the West-South Coast region of Aceh by integrating forecasting, Economic Order Quantity (EOQ), safety stock, and Distribution Requirement Planning (DRP) methods. The research scope covers four distribution centers (DCs), namely Aceh Barat, Nagan Raya, Aceh Barat Daya, and Aceh Selatan, each with distinct demand characteristics: stable, increasing, and declining. The methodology begins with field studies and the collection of secondary data, including historical demand, distribution costs, inventory levels, and lead times. Demand forecasting was conducted using quadratic and cyclical models to estimate requirements for each DC. EOQ calculations were then applied to determine the most economical order quantities, while safety stock was established to maintain inventory availability amid demand uncertainty and lead time variations. These results were integrated into the DRP worksheet, which contains order schedules, net requirements, shipment quantities, and receipt plans for each DC. The findings indicate that DRP effectively accommodates varying demand patterns across DCs, thereby minimizing the risk of overstocking and stockouts. From a cost perspective, a comparison between the company’s actual conditions and the DRP scenario revealed significant efficiency improvements: total distribution costs decreased from IDR 307,227,778 to IDR 301,579,831, yielding savings of IDR 5,647,947 or 1.84%. In conclusion, the application of DRP integrated with forecasting, EOQ, and safety stock enhances distribution cost efficiency while strengthening the reliability of the company’s supply chain. The practical implication of this research highlights the importance of adopting DRP on a continuous basis to enable companies to respond more adaptively, systematically, and efficiently to demand fluctuations and geographic challenges.