IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-140-1_53.html

Anticipating the Scarcity of Food Commodity to Sufficient Availability for the Community in East Java with a Comparison Approach to Forecasting Artificial Neural Networks and Exponential Smoothing

In: Proceedings of the 2022 Brawijaya International Conference (BIC 2022)

Author

Listed:
  • Agus Widodo

    (Brawijaya University, Mathematics and Natural Science)

  • Marsudi

    (Brawijaya University, Mathematics and Natural Science)

  • Dwija Wisnu Brata

    (Brawijaya University, Mathematics and Natural Science)

  • Nahlia Rakhmawati

    (Brawijaya University, Mathematics and Natural Science)

  • Pramudya Adi Wardana

    (Brawijaya University, Mathematics and Natural Science)

Abstract

This research was conducted to predict food commodity prices which include beef prices, medium quality rice price data, chicken egg prices, sugar prices, branded cooking oil prices, bulk cooking oil prices, curly red chili prices, garlic prices, shallot prices and price of grilled chicken the research carried out has a contribution to the commodity variables which are added as part of the factors causing food shortages in 2021, whereas in research related to predictions as was done by previous researchers that variables related to activity objects become a reference in the prediction process. This research was conducted by analyzing food commodity price data taken from the weekly period, namely December 2020 (IV)–April 2022 (I) in East Java Province using the exponential smoothing method. From the results of the analysis it is known that the smallest MAPE (Mean Absolute Percentage Error) ranges from 0.22%–2.44%, which means that the prediction accuracy of food ingredients using the triple exponential smoothing method is very high, which is greater than 97.66% so that it can be used as a recommendations in forecasting food commodity prices for the next period.

Suggested Citation

  • Agus Widodo & Marsudi & Dwija Wisnu Brata & Nahlia Rakhmawati & Pramudya Adi Wardana, 2023. "Anticipating the Scarcity of Food Commodity to Sufficient Availability for the Community in East Java with a Comparison Approach to Forecasting Artificial Neural Networks and Exponential Smoothing," Advances in Economics, Business and Management Research, in: Yusfan Adeputera Yusran & Femiana Gapsari Madhi Fitri & Titin Andri Wihastuti & Fajar Ari Nugroho & (ed.), Proceedings of the 2022 Brawijaya International Conference (BIC 2022), pages 529-540, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-140-1_53
    DOI: 10.2991/978-94-6463-140-1_53
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:advbcp:978-94-6463-140-1_53. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.