Model of Inventory Planning Using Monte Carlo Simulation in Retail Supermarket with Consider To Competitors and Stimulus Strategies
DOI:
https://doi.org/10.37385/jaets.v4i1.1093Keywords:
Inventory Planning, Monte Carlo Method, RetailAbstract
Retail Supermarket is a retail company that provides various types of products to meet the primary needs of the community or people, such as food needs, various cleaning products, snacks, beverages, cosmetics, and many others. The growing retail business requires continously managed in retail company to work more effectively and efficiently in order to be able to face intense business competition so that business continuity can be maintained. The continuity of the company can be maintained if it is managed properly and has proper planning and control. Proper and careful planning followed by good control will continuously make the company's goal of achieving maximum profit achievable. This study will provide a proposal for inventory planning model using the Monte Carlo simulation method by paying attention to competitors and stimulus strategies, which can be used to predict sales for the next period so that the amount of inventory can be planned properly.
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References
A. M. Law and W. D. Kelton, Simulation Modelling and Analysis, USA: Mcgraw-hill, 2000.
Asana, I. M. D. P., Radhitya, M. L., Widiartha, K. K., Santika, P. P., & Wiguna, I. K. A. G. (2020, February). Inventory control using ABC and min-max analysis on retail management information system. In Journal of Physics: Conference Series (Vol. 1469, No. 1, p. 012097). IOP Publishing.
Assauri, S. (2016). Manajemen Operasi Produksi. Jakarta: Rajawali Pers.
Foster, B. (2008). Retail Managemen. 1st ed. Bandung: Alfabeta
Frenkel, D. (2004). Introduction to Monte Carlo Methods. Computational Soft Matter: From Synthetics Polymers to Proteins, Vol.23, ISBN 3-00-012641-4, pp.29-60.
Fuertes, G., Alfaro, M., Vargas, M., Gutierrez, S., Ternero, R., & Sabattin, J. (2020). Conceptual framework for the strategic management: a literature review—descriptive. Journal of Engineering, 2020.
Heizer, J., & Render, B. (2015). Operation Manajemen. Jakarta: Salemba Empat.
Hutahaean, H. D. (2018). Analisa metode Monte Carlo untuk memprediksi tingkat kehadiran mahasiswa dalam perkuliahan (studi kasus: STMIK pelita nusantara). Journal Of Informatic Pelita Nusantara, 3(1).
Indrajit, R. E., & Djokropranoto, R. (2005). Manajemen Persediaan. Jakarta: Grasindo.
Lucic, A., Haned, H., & de Rijke, M. (2020, January). Why does my model fail? contrastive local explanations for retail forecasting. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (pp. 90-98).
Leepaitoon, S., & Bunterngchit, C. (2019). The application of Monte Carlo simulation for inventory management: A case study of a retail store. International Journal of the Computer, the Internet and Management, 27(2), 67-83.
Luengo, D., Martino, L., Bugallo, M., Elvira, V., & Särkkä, S. (2020). A survey of Monte Carlo methods for parameter estimation. EURASIP Journal on Advances in Signal Processing, 2020(1), 1-62.
Montororing, Y. D. R. & Nurprihatin, F. (2021). Model of Quality Control Station Allocation With Consider Work In Process, and Defect Probability Of Final Product. IOP Conference Series: Journal of Physics vol 1811 (IOP Publishing Ltd)
Montororing, Y. D. R., Widyantoro, M., Muhazir., A. (2022). Production Process improvements to minimize product defects using DMAIC six sigma statistical tool and FMEA at PT. KAEF. IOP Conference Series: Journal of Physics vol 2157 (IOP Publishing Ltd).
Naim, M. A., & Donoriyanto, D. S. (2020). Pengendalian Persediaan Obat di Apotek XYZ Dengan Menggunakan Metode Monte Carlo. Jurnal Manajemen Industri dan Teknologi, 1.
Oh. M.S. and Berger. J.o (1992). Adaptive Importance Sampling In Monte Carlo Integration. Journal Of Statistical Computation And Simulation. 41. 143-168.
Prasetyowati, E. (2016). Aplikasi Simulasi Persediaan Teri Crispy Prisma Menggunakan Metode Monte Carlo. JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia), 1(1).
Purwatinah, A. (2021). Pengelolaan Bisnis Ritel. Jakarta: Grasindo.
Ramadan. H.,Gio. P. U., & Rosmaini. E. (2020). Monte Carlo Simulation Approach To Determine The Optimal Solution Of Probabilistic Supply Cost. Journal of Research in Mathematics Trends and Technology. Vol.2 No.1. 1-6
R. J. Tersine. (1994). Principles of Inventory and Materials Management, 4th Ed., USA: Prentice Hall, Inc
R. Y. Rubinstein and D. Kroese, Simulation and the Monte Carlo Method, New York: John Wiley & Sons, 1981.
Safitri, D., Dahdah, S. S., & Andesta, D. (2020). Penerapan Metode Monte Carlo Pada Perencanaan Jumlah Produksi Pestisida (Studi Kasus: PT. Petrokimia Kayaku Plant Cair 1). JUSTI (Jurnal Sistem dan Teknik Industri), 1(1), 96-100.
Sridadi, B. (2009). Pemodelan dan Simulasi Sistem. Bandung: Informatika.
Siregar, L., Herlina, L., & Kulsum. (2014). Pengendalian Persediaan Bahan Bak di PT. ABC Dengan Model Q Back Order Menggunakan Metode Monte Carlo. Jurnal Teknik Industri Untirta.
Xue, X., Dou, J., & Shang, Y. (2020). Blockchain-driven supply chain decentralized operations–information sharing perspective. Business Process Management Journal.