DESIGN OF AN INFORMATION SYSTEM FOR FORECASTING FABRIC DEMAND (CASE STUDY AT CAHAYA SANDANG)

Authors

  • Geraldy Setiawan Parahyangan Catholic University, Indonesia
  • Dedy Suryadi

DOI:

https://doi.org/10.29040/ijebar.v8i2.13055

Abstract

In the course of weekly fabric procurement from suppliers, Cahaya Sandang frequently encounters challenges in determining the optimal quantity of fabrics to be ordered. The uncertainty surrounding order quantities has led to a loss of consumer confidence for Cahaya Sandang. To address this issue, a research initiative was undertaken, focusing on the development of an information system for forecasting fabric sales at the Cahaya Sandang Store. The fabric sales forecasting system was designed using Python, incorporating various forecasting methodologies such as moving average, exponential smoothing, linear regression, Autoregressive Integrated Moving Average (ARIMA), and Long Short Memory Term (LSTM). These designated forecasting methods are exclusively applied to predict cloth sales for the subsequent week. The determination of forecasting methods was based on the Mean Absolute Percentage Error (MAPE) values derived from the existing forecasting models. The findings affirm the efficacy of the five employed methods, demonstrating a maximum error value below 10% for the prediction of Cahaya Sandang fabric sales. By implementing this fabric sales forecasting system, the decision-making process regarding fabric orders from suppliers is expected to become more streamlined and targeted.

Author Biography

Geraldy Setiawan, Parahyangan Catholic University

Industrial Engineering Department

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Published

2024-06-26

How to Cite

Setiawan, G., & Suryadi, D. (2024). DESIGN OF AN INFORMATION SYSTEM FOR FORECASTING FABRIC DEMAND (CASE STUDY AT CAHAYA SANDANG). International Journal of Economics, Business and Accounting Research (IJEBAR), 8(2). https://doi.org/10.29040/ijebar.v8i2.13055

Issue

Vol. 8 No. 2 (2024): IJEBAR, VOL. 08 ISSUE 02, JUNE 2024

Section

Articles

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