Integrasi Model Inventori EOQ dan Time Series Forecasting Untuk Sistem Inventori Optimal

Authors

  • Rizka Britania Universitas Bina Nusantara
  • Amir Tjolleng Universitas Bina Nusantara
  • Salma Ardiana Putri Universitas Bina Nusantara

DOI:

https://doi.org/10.30997/jvs.v10i1.13310

Keywords:

EOQ Model, Forecast, Inventory

Abstract

This research aims to evaluate the existing inventory system and determine the optimal inventory system for the future at PT XYZ. The methods used are Economic Order Quantity (EOQ) integrated with time series forecasting. The selection of products studied is based on inbound and outbound volumes in the warehouse. The application of the EOQ method to the five study products resulted in an optimal order quantity for the existing conditions of 925 drums, 737 drums, 612 drums, 705 drums, and 729 drums for products A, B, C, D, and E. There is a potential saving in total inventory costs of 24% generated by the EOQ model compared to the current inventory system in the company. Historical demand data shows a seasonal stationary pattern. Forecast for the coming year was conducted and used in calculating the optimal order quantity for the coming year, which are 775 drums, 891 drums, 611 drums, and 728 drums for products A, B, C, and E. This research can enrich the literature related to EOQ and provide input for companies regarding the potential savings that can be made, and information on inventory system needs for the future.

  

ABSTRAK

Penelitian ini bertujuan mengevaluasi sistem inventori eksisting dan menentukan sistem inventori optimal untuk masa mendatang pada PT XYZ. Metode yang digunakan adalah Economic Order Quantity (EOQ) yang diintegrasikan dengan time series forecasting. Pemilihan produk yang dikaji didasarkan pada volume inbound dan outbound di gudang. Penerapan metode EOQ pada lima produk kajian memberikan hasil kuantitas pemesanan optimal untuk kondisi eksisting sejumlah 925 drum, 737 drum, 612 drum, 705 drum, dan 729 drum untuk produk A, B, C, D, dan E. Terdapat potensi penghematan total ongkos inventori sebesar 24% yang dihasilkan model EOQ dibandingkan dengan sistem inventori yang saat ini berlangsung di perusahaan. Data historis demand menunjukkan adanya pola seasonal stationer. Forecast untuk satu tahun mendatang dilakukan dan digunakan dalam menghitung kuantitas order optimal untuk tahun mendatang, yaitu sebesar 775 drum, 891 drum, 611 drum, dan 728 drum untuk produk A, B, C, dan E. Penelitian ini dapat memperkaya literatur terkait EOQ, dan memberikan masukan bagi perusahaan terkait potensi penghematan yang dapat dilakukan, dan informasi kebutuhan sistem inventori untuk masa mendatang.

References

Arnold, J. R. T., Chapman, S. N., & Clive, L. M. (2008). Introduction to Materials Management (6th ed.). New Jersey: Pearson Prentice Hall.

Baraka, J. M., & Yadavalli, S. V. (2022). Inventory management concepts and implementations : a systematic review. South African Journal of Industrial Engineering, 32(2), 15–36. https://doi.org/10.7166/33-2-2527

Darmadi. (2020). Penerapan Pengendalian Persediaan Metode Economic Order Quantity (EOQ) di PT Wijaya Metalindo Work. Kaizen : Management Systems & Industrial Engineering Journal, 3(1), 16–24. https://doi.org/10.25273/kaizen.v3i1.6647

Hamisi, S. (2011). Challenges and opportunities of Tanzanian SMEs in adapting supply chain management. African Journal of Business Management, 5(4), 1266–1276. https://doi.org/10.5897/AJBM10.704

Heizer, J., Render, B., & Munson, C. (2017). Principles of Operations Management: Sustainability and Supply Chain Management (10th ed.). Harlow: Pearson Education.

Inasari, F., Korawijayanti, L., & Farizi, M. A. L. (2023). Implementation of The Economic Order Quantity (EOQ) Method on CV Anugrah Sakti. Applied Accounting and Management Review, 2(1), 43–50. https://doi.org/10.32497/aamar.v2i1.4412

Khobragade, P., Selokar, R., Maraskolhe, R., & Talmale, M. (2018). Research paper on Inventory management system. International Research Journal of Engineering and Technology, 5(4), 252–254.

Liu, Z., Zhao, Y., Yang, S., Ju, J., Yang, L., Li, R., Zhang, J., & Lu, W. (2024). Time Series Analysis of Product Demand Forecasting and Inventory Optimization on E-commerce Platforms. Journal of Electronics and Information Science, 9(1), 49–54. https://doi.org/10.23977/jeis.2024.090108

Nahmias, S., & Olsen, T. L. (2015). Production and Operation Analysis (7th ed.). Illinois: Waveland Press.

Nemtajela, N., & Mbohwa, C. (2017). Relationship between inventory management and uncertain demand for fast moving consumer goods organisations. Procedia Manufacturing, 8, 699–706. https://doi.org/10.1016/j.promfg.2017.02.090

Oktaviani, A., Subawanto, H., & Purba, H. H. (2017). The Implementation of ABC Classification and (Q,R) with Economic Order Quantity (EOQ) Model on the Travel Agency. Comtech, 8(1), 45–54. https://doi.org/10.21512/comtech.v8i1.3778

Panda, S. K., & Mohanty, S. N. (2016). Time Series Forecasting and Modelling of Food Demand Supply Chain based on Regressors Analysis. IEEE Access, 4, 1. https://doi.org/10.1109/ACCESS.2023.3266275

Render, B., Stair, R. M., Hanna, M. E., & Hale, T. S. (2018). Quantitative Analysis for Management (13th ed.). Harlow: Pearson Education.

Ritawiyati, Maryanti, S., & Thamrin, M. (2018). Metode Economic Order Quantity (EOQ) sebagai Dasar Pengendalian Bahan Baku Tepung Terigu (Studi Kasus Home Industry Roti Sekarsari Kampar). Jurnal Ilmu Komputer Dan Bisnis, 9(2), 2059–2069.

Russel, R. S., & Taylor, B. W. (2011). Operation Management: Creating Value along the Supply Chain (7th ed.). New Jersey: John Wiley & Sons.

Shang, H. L. (2012). Functional time series approach for forecasting very short-term electricity demand. Journal of Applied Statistics, 40(1), 152–168. https://doi.org/10.1080/02664763.2012.740619

Sohail, N., & Sheikh, T. H. (2018). A Study of Inventory Management System Case Study. Jour of Adv Research in Dynamical & Control Systems, 10(September), 1176–1190.

Sople, V. V. (2012). Logistics Management: The Supply Chain Imperative (3rd ed.). Uttar Pradesh: Pearson India Education.

Susanti, & Kalalo, M. Y. B. (2023). Analisis penerapan metode economic order quantity sebagai upaya pengendalian persediaan bahan baku pada UD Imanuel Tompaso Baru Susanti. Manajemen Bisnis Dan Keuangan Korporat, 1(2), 112–127. https://doi.org/10.58784/mbkk.66

Vrat, P. (2014). Materials Management: An Integrated Systems Approach. New Delhi: Springer.

Wang, Y. (2023). Overview of Logistics Demand Forecasting Methods. Frontiers in Business, Economics and Management, 9(2). https://doi.org/10.54097/fbem.v9i2.9293

Downloads

Published

2024-06-25

How to Cite

Britania, R., Tjolleng, A. ., & Ardiana Putri, S. (2024). Integrasi Model Inventori EOQ dan Time Series Forecasting Untuk Sistem Inventori Optimal . Jurnal Visionida, 10(1), 78–93. https://doi.org/10.30997/jvs.v10i1.13310

Issue

Section

Articles
Abstract viewed = 5 times