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All Journal SISFOTENIKA
Dwi, I Kadek
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering

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The Optimisation of Stock Management: Design of an AI-Driven Inventory System Putra, Cendra Devayana; Utami, Ardhini Warih; Dwi, I Kadek; Prayoga, Riza Akhsani Setyo; Basatha, Rizky; Muhammad Sonhaji Akbar
SISFOTENIKA Vol. 15 No. 2 (2025): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/sisfotenika.v15i2.543

Abstract

The frozen food industry has witnessed remarkable growth in recent years, driven by increasing urbanization and the demand for convenient, ready-to-eat meals. Despite this upward trend, many businesses in the sector struggle with inefficient stock management, particularly in forecasting daily demand due to fluctuating consumer behavior and unpredictable external factors. This study proposes an end-to-end artificial intelligence-based stock forecasting system aimed at optimizing inventory management for frozen food businesses. By adopting the Design Thinking approach, this research places users—both consumers and internal stakeholders—at the center of the problem-solving process to uncover key operational pain points. The study explores recent technological advancements, including augmented reality, RFID, and blockchain, and integrates them into a practical framework tailored to small and medium enterprises (SMEs). Through qualitative analysis and system prototyping, the research identifies essential features for an intelligent stock management system and demonstrates how a user-centric approach can drive innovation and improve business performance. The findings offer valuable insights into the development of adaptive, data-driven solutions in the rapidly evolving frozen food sector.
Co-Authors Ardhini Warih Utami, Ardhini Warih Muhammad Sonhaji Akbar Putra, Cendra Devayana Riza Akhsani Setyo Prayoga Rizky Basatha