Forecasting the Consumption of Welding Consumables Using Markov Chain Models for Inventory Optimization at PT Buana Cipta Mandala
DOI:
https://doi.org/10.62375/jsintak.v4i2.822Kata Kunci:
Markov Chain, Inventory Optimization, Welding ConsumablesAbstrak
This study aims to analyze the monthly withdrawal patterns of welding consumables (welding cup, black lens, clear lens) and develop a forecasting model to support inventory policy optimization at PT Buana Cipta Mandala, Batam. Employing a quantitative case study approach with time series data from Januari to August 2025. Withdawal volume data was categorized into three states (low, medium, high). The Markov chain model was constructed by calculating transition frequency matrices, transition probability matrices, and steady-state probabilities for each item. Preliminary descriptive statistical analysis was conducted to understand data characteristics. The findings reveal distinct transition patterns. The welding cup exhibits a rapid cycle dynamic with a steady-state probability 0.286 for low, 0.286 for medium, and 0.428 for high state, indicating a long term dominance of the high state. Conversely, the welding lenses have a transition matrix where the low state acts as an absorbing state, with a steady-state probability 1 for low, and 0 for medium and high state, predicting a convergence of demand to a low level. The resulting model recommends differentiated inventory strategies. A moderate to high stock policy with sufficient safety stock for welding cups, and a lean inventory policy based on base demand for welding lenses. The application of this Markov chain model provides a quantitative foundation for more precise procurement decision making, reducing the risks of stockout and overstocking, thereby supporting supply chain efficiency and shipyard operations.
Referensi
R. Dwi Oktavia and N. Hayati, “Analysis of Fabrication Work Progress Based on Time Duration and Component Weight at PT. DIP Engineering,” Jurnal Sintak, vol. 4, no. 1, 2025, doi: 10.62375/jsintak.v4i1.719.
J. Heizer, B. Render, C. L. Munson, and P. Griffin, Operations management: Sustainability and supply chain management20, 14th ed. Pearson, 2022.
R. G. Schroeder and S. Meyer. Goldstein, Operations management in the supply chain: decisions and cases. McGraw-Hill Education, 2021.
E. A. Silver, D. F. Pyke, and D. J. Thomas, Inventory and production management in supply chains. CRC Press, 2016.
R. J. Hyndman, “Forecasting: principles and practice.”
N. Hayati, E. Sulistyono, and B. P. Utami, “Optimizing Classroom Allocation using Markov Chain Model for Shifted Lecture Schedules,” Jurnal Matematika UNAND, vol. 15, no. 1, pp. 17–29, Jan. 2026, doi: 10.25077/jmua.15.1.17-29.2026.
R. Panneerselvam, Operations research. PHI Learning Pvt. Ltd., 2023.
N. Hayati, E. Sulistyono, and R. Gusrita, “Markov Chain Analysis of Bank Customer Migration: Implication for Financial Inclusion in Maritime Economies,” vol. 9, no. 4, pp. 1142–1152, 2025, doi: 10.31764/jtam.v9i4.32121.
N. Hayati, A. Setyo Anggraeni, and E. Sulistyono, “A Daily Transition Analysis of Disaster Events in Riau Islands using Markov Chains: Dominant Disaster Identification and Risk Assessment,” vol. 10, no. 1, pp. 1591–1600, 2026, doi: 10.31764/jtam.v10i1.34024.
Q. Hu, J. E. Boylan, H. Chen, and A. Labib, “OR in Spare Parts Management: A Review.”
S. Van der Auweraer, R. N. Boute, and A. A. Syntetos, “Forecasting spare part demand with installed base information: A review,” Int. J. Forecast., vol. 35, no. 1, pp. 181–196, Jan. 2019, doi: 10.1016/j.ijforecast.2018.09.002.
N. Hayati, M. Kiftiah, and B. Prihandono, “Application of the Jukes Cantor Model in Determining the Probability of Nitrogen Bases in the Offspring of an Individual (Aplikasi Model Jukes Cantor dalam Menentukan Peluang Basa Nitrogen Keturunan Suatu Individu),” Bimaster: Buletin Ilmiah Matematika, Statistika dan Terapannya, vol. 5, no. 2, pp. 119–128, 2016.
E. Seabrook and L. Wiskott, “A Tutorial on the Spectral Theory of Markov Chains,” Nov. 01, 2023, MIT Press Journals. doi: 10.1162/neco_a_01611.
I. Mangku, Proses Stokastik Dasar, vol. 1. Bogor: PT. Penerbit IPB Press, 2022.
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Hak Cipta (c) 2026 Muhammad Reza Rafella Palevi, Nahrul Hayati

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