Average Forecasting Analysis of Premium Quality Rice Prices at the Milling Level Using the Moving Average Time Series Method

https://doi.org/10.61487/jiste.v2i4.114

Authors

  • Muhammad Reza Aulia Universitas Teuku Umar
  • Abdul Muzammil Universitas Teuku Umar
  • Wira Santia Universitas Teuku Umar
  • Auliyah Ulpah Universitas Teuku Umar
  • Ermanica Ermanica Universitas Teuku Umar
  • Nuru Badriah Universitas Teuku Umar
  • Aidar Aidar Universitas Teuku Umar

Keywords:

rice price, central statistics agency (bps), forecasting

Abstract

The aim of this research is to estimate the average price of premium-quality rice at the mill level until August 2025. From October to November 2023, the study in Meulaboh, West Aceh Regency, analyzed the price of premium quality rice at the milling level using BPS secondary data. We employed a quantitative descriptive analysis, leveraging time series analysis to uncover trends and forecast future rice prices. Time series data, which tracks changes over time in variables such as production, prices, and sales, helps identify trends, constants, or seasonal patterns. Since the price of premium rice at the milling level consistently increased from January 2022 to August 2023, we classify this data as trend data. The analysis used the exponential smoothing model and the weighted moving average to calculate the expected future prices. The moving average method, based on the analysis of average data, forecasts the mean squared error (MSE), mean absolute deviation (MAD), mean absolute percent error (MAPE), and mean error of estimation (MFE). The moving average method forecasts the average price of premium quality rice from January 2022 to August 2023. Based on the forecast results, there will be fluctuations in accuracy during this period, with MAPE values ranging from 0.015 to 0.094. The dotted line displays the average price results, while the straight line indicates the actual price. The stars indicate the actual price in the forecast graph, which displays the trend of premium rice prices at the milling level. This final assessment shows how well the forecasting model performs and provides information on the trend of premium rice prices to help with future decision-making.

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Published

2024-12-12

How to Cite

Aulia, M. R., Muzammil, A., Santia, W., Ulpah, A., Ermanica, E., Badriah, N., & Aidar, A. (2024). Average Forecasting Analysis of Premium Quality Rice Prices at the Milling Level Using the Moving Average Time Series Method. Journal of Information System, Technology and Engineering, 2(4), 349–355. https://doi.org/10.61487/jiste.v2i4.114

Issue

Vol. 2 No. 4 (2024): JISTE

Section

Articles
Copyright & Licensing

Copyright (c) 2024 Muhammad Reza Aulia, Abdul Muzammil, Wira Santia, Auliyah Ulpah, Ermanica Ermanica, Nuru Badriah, Aidar Aidar

Creative Commons License

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