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All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) Jurnal Geografi Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat GUYUB: Journal of Community Engagement Andalasian International Journal of Applied Science, Engineering, and Technology CONSEN: Indonesian Journal of Community Services and Engagement International Journal of Multidisciplinary Research of Higher Education (IJMURHICA) Journal of Hypermedia & Technology-Enhanced Learning Journal of Authentic Research
Sandra, Randi Proska
Universitas Negeri Padang
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Physics Public Health Social Sciences Other

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Journal : Journal of Hypermedia

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Web-Based Inventory Management System for Educational Training: Integrating EOQ and ARIMA for Data-Driven Learning Syamsi, Alkindi; Irfan, Dedy; Novaliendry, Dony; Sandra, Randi Proska
Journal of Hypermedia & Technology-Enhanced Learning Vol. 4 No. 1 (2026): Journal of Hypermedia & Technology-Enhanced Learning—Future Education
Publisher : Sagamedia Teknologi Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58536/j-hytel.218

Abstract

Manual inventory recording and heuristic ordering practices remain common among Micro, Small, and Medium Enterprises (MSMEs), often leading to inaccurate demand estimation, excessive holding costs, and stockouts. This study develops and evaluates a web-based inventory information system that integrates Autoregressive Integrated Moving Average (ARIMA) forecasting with the Economic Order Quantity (EOQ) model to improve decision accuracy and cost efficiency. The system uses CodeIgniter 3 and MySQL and incorporates a Python-based time-series forecasting engine. Historical sales data were modeled using ARIMA, and the optimal specification was selected based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The ARIMA(1,1,1) model achieved a Mean Absolute Percentage Error (MAPE) of 8.47%, indicating high forecasting accuracy for operational planning. The forecasted annual demand was integrated into the EOQ framework to determine the optimal order quantity, Reorder Point (ROP), and probabilistic Safety Stock. A one-year cost simulation demonstrated that the EOQ-based policy reduced total inventory costs by 22.73% compared with the existing approach. Functional validation through Black-Box testing confirmed full compliance with specified requirements. These findings demonstrate that integrating predictive analytics with classical inventory optimization enhances operational efficiency and reduces total inventory cost. The system provides a practical, data-driven inventory management framework for MSMEs undergoing digital transformation.
Co-Authors Agariadne Dwinggo Samala Ahmaddul Hadi Apriliyanti, Resti Aviola, Rawim Puja Azmi, Arafil Bayu Wijayanto Budi Sunaryo Cakranata, Raden Galuh Garhadi Dedy Irfan Dony Novaliendry Efrizon Efrizon Fadhli Ranuharja Farezi, Ridho Al Febriani, Natasya Fitrian, Rahmat Geovanne Farell Huda, Yasdinul Ika Parma Dewi Karina, Lani Dwi Kurniawan, Alan Lativa Mursyida Maiyenti, Elisa Marta, Rizkayeni Mubai, Akrimullah Muhammad Ismail Mursyida, Lativa Nerurkar, Pranav Prihantarto, Wikan Jaya Putri, Mutiara Amelia Putri, Yusra Aprila Rahmawati, Chindy Reihan Hanafi Wiyanatra Ryan Fikri Sriharta, M Sunaryo, Budi Suriani, Ari Syafrijon Syafrijon, Syafrijon Syamsi, Alkindi Wiyanatra, Reihan Hanafi Yasdinul Huda Yosi, Febri Zulfadli Zulfadli Zulfadli Zulfadli