Home
World Journal of Advanced Research and Reviews
International Journal with High Impact Factor for fast publication of Research and Review articles

Main navigation

  • Home
    • Journal Information
    • Editorial Board Members
    • Reviewer Panel
    • Abstracting and Indexing
    • Journal Policies
    • Our CrossMark Policy
    • Publication Ethics
    • Issue in Progress
    • Current Issue
    • Past Issues
    • Instructions for Authors
    • Article processing fee
    • Track Manuscript Status
    • Get Publication Certificate
    • Join Editorial Board
    • Join Reviewer Panel
  • Contact us
  • Downloads

eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

Optimizing inventory management and demand forecasting system using time series algorithm

Breadcrumb

  • Home
  • Optimizing inventory management and demand forecasting system using time series algorithm

Alexandra An Pavon Arnaiz 1, Lovely Samuele Cristal 1, Antonette Obligado Fernandez 1, Mark Rowie Flores Gubaton 1, *, Domingo Valenzuela Tanael 2 and Criselle Jose Centeno 2

1 College of Computer Studies, Global Reciprocal Colleges, Philippines.
2 Information Technology Department, Faculty of Assistant Professor, Pamantasan ng Lungsod ng Maynila, Philippines.\
 
Research Article
World Journal of Advanced Research and Reviews, 2023, 20(03), 021-027
Article DOI: 10.30574/wjarr.2023.20.3.2456
DOI url: https://doi.org/10.30574/wjarr.2023.20.3.2456
 
Received on 19 October 2023; revised on 28 November 2023; accepted on 30 November 2023
 
In the rapidly evolving business landscape, effective inventory management and meeting customer demands rely heavily on accurate forecasting. While technology automates parts of inventory control, human expertise remains vital in decision-making for forecasting. Building supplier relationships, monitoring market trends, and adaptable supply chains are crucial too. Accurate demand forecasting reduces costs, streamlines operations, and boosts customer satisfaction. Therefore, companies must carefully review their forecasting methods to stay competitive. Researchers are addressing the lack of data on inventory and forecasting by focusing on implementing time series algorithms, recognizing their crucial role in optimizing these processes. This academic pursuit has led researchers to develop a user-friendly system tailored for improved inventory management, integrating a feature set dedicated to demand forecasting. The project aims to streamline user operations by offering an intuitive platform that facilitates seamless navigation. By encompassing forecasting capabilities, the system empowers businesses to accurately predict their future product requirements. The primary objective of this initiative is to simplify inventory procedures while enabling users to proactively meet upcoming demands effectively. While conducting the study, the researcher considered the first problem in how the user will use the inventory system in a more user-friendly manner. The second problem that the researchers conducted was manual input, and it will cost more when the documents are not organized. Lastly, the highest problem that the inventory management conducted was the overseers of the products by excessive inventory, low stocks, and expired products. The researchers use some of the sub-characteristics of ISO 25010 that are appropriate for evaluating inventory management. After evaluation, the sub-characteristics of functional stability garnered an overall weighted mean of 3.90. The compatibility and usability garnered an overall weight of 3.89. Reliability garnered an overall weight of 3.66. Lastly, maintainability was overall weighted at 3.63. The confusion matrix was used with the help of the tool of Weka Software using the scheme of function. Simple Logistics. The evaluation on the training set has a summary of correctly classified instances of 89.4737% and incorrectly classified instances of 10.5263%, which indicates that the application has an accurate algorithm.
 
Inventory; Forecasting; Time-series; Supplies; Reorder Point
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2023-2456.pdf

Preview Article PDF

Alexandra An Pavon Arnaiz, Lovely Samuele Cristal, Antonette Obligado Fernandez, Mark Rowie Flores Gubaton, Domingo Valenzuela Tanael and Criselle Jose Centeno. Optimizing inventory management and demand forecasting system using time series algorithm. World Journal of Advanced Research and Reviews, 2023, 20(3), 021-027. Article DOI: https://doi.org/10.30574/wjarr.2023.20.3.2456

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

Get Certificates

Get Publication Certificate

Download LoA

Check Corssref DOI details

Issue details

Issue Cover Page

Editorial Board

Table of content

Copyright © 2026 World Journal of Advanced Research and Reviews - All rights reserved

Developed & Designed by VS Infosolution