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All Journal Jurnal Sistem dan Informatika Jurnal Sains Teknologi dan Sistem Informasi SISFOTENIKA
Muhammad Sonhaji Akbar
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering

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Journal : SISFOTENIKA

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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.
Pemanfaatan Deep Learning dalam Kurikulum Pembelajaran Abad 21: Sebuah Tinjauan Literatur Zain, Muhammad; 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.v15i2.577

Abstract

The transformation of education today is highly dependent on the use of technology, aiming to prepare students who are skilled, adaptive, and ready to compete in the industrial world. This study aims to systematically examine the use, role, and challenges of implementing Deep Learning as part of Artificial Intelligence in the renewed educational curriculum. The study employs a Systematic Literature Review, and its data comes from 28 scientific articles, journals, and research reports that examine the application of Deep Learning technology in education. The research data were analyzed based on themes to identify roles, uses, benefits for 21st-century skills, and difficulties in implementation. The results of the study indicate that Deep Learning plays a significant role in learning that is tailored to student needs through an adaptive system, helps develop appropriate skills in the 21st century (4C), and improves methods for analyzing educational data for early intervention.
Co-Authors Ardhini Warih Utami, Ardhini Warih Dwi, I Kadek Ersha Aisyah Elfaiz Monica Cinthya Muhammad Zain, Muhammad Putra, Cendra Devayana Riza Akhsani Setyo Prayoga Rizky Basatha Rizky Basatha Siti Rochimah