Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Advances in Business & Industrial Marketing Research
Ginandia Ariesta
Universitas Primagraha, Serang, Indonesia
Economics, Econometrics & Finance

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Smart Warehouse Ecosystem: An IoT-Based Framework for Real-Time Environmental Monitoring in a Nutrition Fulfillment Service Unit (SPPG) Warehouse Geby Ayu Fadhilah; Ginandia Ariesta; Ahmad Rufa'i; Deddy Rusdiansyah; Syarif Hidayat
Advances in Business & Industrial Marketing Research Vol. 4 No. 2 (2026): February - May
Publisher : Yayasan Pendidikan Bukhari Dwi Muslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60079/abim.v4i2.856

Abstract

Purpose: This conceptual and simulation-based study aims to examine the potential digital transformation of the logistics system at the Kasemen SPPG Warehouse. It specifically investigates the ability of RFID integration to reduce inaccuracies in food inventory data, evaluates the responsiveness of an IoT-based network architecture using the MQTT protocol for environmental early-warning transmission, and measures automation-driven cycle-time efficiency in inbound and outbound logistics processes. Research Method: This study applies a Research and Development (R&D) approach, focusing on conceptual framework design and performance evaluation using secondary data. The analysis includes Inventory Record Inaccuracy (IRI) measurement using RMSE, evaluation of notification responsiveness via MQTT transmission delay, and time-motion analysis of inbound and outbound cycles, supported by an automated FEFO algorithm. Results and Discussion: The simulation results provide preliminary conceptual support for the proposed operational hypotheses. IRI decreased by 88.86%, from 6.91 to 0.77 RMSE units. Notification responsiveness improved by 99.98%, from 21,600 seconds in the manual system to 2.2 seconds using MQTT. Automation also reduced cycle time by 92.59% in inbound activities and 93.33% in outbound activities. Implications: The findings offer a practical blueprint for shifting warehouse operations from reactive to preventive, reducing the risk of food waste, and supporting digitally standardized logistics SOPs. Originality: This study presents an integrated IoT-based Smart Warehouse model that combines RFID, MQTT, and automated FEFO to support food logistics decision-making.
Co-Authors Ahmad Rufa'i Deddy Rusdiansyah Geby Ayu Fadhilah Syarif Hidayat