Inventory Forecasting Analysis using The Weighted Moving Average Method in Go Public Trading Companies

English

Authors

  • Erycha Puspitasari Politeknik Negeri Malang
  • Nurafni Eltivia Politeknik Negeri Malang
  • Nur Indah Riwajanti Politeknik Negeri Malang

DOI:

https://doi.org/10.54408/jabter.v2i3.160

Keywords:

Inventory, Forecasting, Weighted Moving Average Method

Abstract

This research aims to analyze inventory forecasting using the weighted moving average method and then compare the trading companies' patterns. The research method used is quantitative descriptive with secondary data of inventory in the period 2018-2022 which provide quarterly. This research uses the weighted moving average method to calculate forecasting of inventory by Microsoft Excel data analysis techniques. This research shows the highest inventory forecasting on PT Sumber Alfaria Trijaya Tbk (AMRT) occurs in the first quarter of 2023 with the amount of 10.537.541 and the lowest forecasting occurs in the second quarter in 2023 with the amount of 10.431.677. The highest inventory forecasting on PT Erajaya Swasembada Tbk (ERAA) occurs in the second quarter of 2023 with the amount of 6.443.525 and the lowest forecasting in the fourth quarter of 2023 with the amount of 6.418.659. The highest inventory forecasting on PT United Tractors Tbk (UNTR) occurs in the third quarter of 2023 with the amount of 12.239.422 and the lowest forecasting in the first quarter of 2023 with the amount of 12.050.681. Based on the study's results, the tracking signal value at AMRT was 2,17, ERAA was 0.01, and UNTR was -0.08. The three companies' results prove that the weighted moving average can be used to determine inventory forecasting for the next period because the tracking signal value is still within the control limits of ±4.

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References

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Published

2023-02-28

How to Cite

Puspitasari, E., Eltivia, N., & Riwajanti, N. I. (2023). Inventory Forecasting Analysis using The Weighted Moving Average Method in Go Public Trading Companies: English. Journal of Applied Business, Taxation and Economics Research, 2(3), 298–310. https://doi.org/10.54408/jabter.v2i3.160

Issue

Vol. 2 No. 3 (2023): February 2023

Section

Articles

License

Copyright (c) 2023 Erycha Puspitasari, Nurafni Eltivia, Nur Indah Riwajanti

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

This journal is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.