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All Journal Kohesi: Jurnal Sains dan Teknologi
Tandiansyah, Tantan
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Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Energy Engineering Other

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PENGENDALIAN PERSEDIAAN SUKU CADANG NUT DENGAN MENGGUNAKAN METODE KLASIFIKASI ABC DAN MODEL Q BACK ORDER DI PT FGH Tandiansyah, Tantan; Nasrullah, Rizky; Fauzi, Muchammad
Kohesi: Jurnal Sains dan Teknologi Vol. 6 No. 10 (2025): Kohesi: Jurnal Sains dan Teknologi
Publisher : CV SWA Anugerah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.3785/kohesi.v6i11.10446

Abstract

This study aims to analyze and optimize the management of nut spare parts inventory at PT FGH using the ABC Classification method and the Q Back order Model. ABC classification is used to group 20 types of spare parts based on the value of fund absorption and frequency of demand, so as to determine management priorities. The analysis results show that 70.66% of the funds are allocated to category A, which includes components with high consumption value and significant demand frequency. Meanwhile, the Q Back order Model is applied to calculate the optimal ordering lot size (q0), safety stock (ss), reorder point (r), and service level (η), with a high level of inventory cost efficiency. The results of applying the Q Back order Model show total cost savings for category A, with the lowest total inventory cost of Rp113,591,283 and the highest of Rp528,899,608. The combination of the ABC Classification method and the Q Back order Model provides an effective solution in managing inventory strategically, minimizing costs, reducing the risk of stock shortages, and maintaining a smooth production process. The implementation of this method can be a reference for more efficient and sustainable inventory management at PT FGH
PERAMALAN PRODUKSI SPARE PART DI PT. XYZ DENGAN MENGGUNAKAN METODE DEKOMPOSISI Tandiansyah, Tantan; Febrianto Maulana, Ferdy; Ihsan, Tiaradia
Kohesi: Jurnal Sains dan Teknologi Vol. 6 No. 10 (2025): Kohesi: Jurnal Sains dan Teknologi
Publisher : CV SWA Anugerah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.3785/kohesi.v6i11.10449

Abstract

The manufacturing industry faces major challenges in managing often uncertain demand fluctuations. This applies to PT. XYZ, a company operated in the production of automotive spare parts. Uncertainty in demand results in the risk of overproduction which increases storage costs or underproduction which has the potential to reduce customer confidence. The aim of this research is to predict production demand implementing the decomposition method, which separates historical data into trend, seasonal, cyclical and random components. This method is able to provide more accurate predictions by utilizing historical data for the last three years. The research results show that there are seasonal trends that influence inventory levels, with peak inventories usually occurring in K1 or K3, while K4 tends to be the period with the lowest inventories. With this method, PT. XYZ can increase production efficiency, minimize operational costs, and optimize production capacity according to market needs. Based on inventory estimates for 2024 and 2025, a consistent fluctuation pattern can be seen every quarter. In 2024, the first quarter (K1) is estimated to have inventory of 23,107 units, which then decreases slightly in K2 to 22,058 units. Inventory increased again in K3 to 23,210 units, before experiencing a significant decline in K4 of 21,602 units. This pattern repeats in 2025, with K1 showing an increase to 24,381 units, followed by a decrease in K2 of 23,258 units. Inventory rose again in K3 to 24,455 units and fell again in K4 by 22,746 units.
Co-Authors Febrianto Maulana, Ferdy Muchammad Fauzi Nasrullah, Rizky Tiaradia Ihsan