Design of AiStock Application Based on Artificial Intelligence for Stock Management Efficiency of Digital Retail SMEs
DOI:
https://doi.org/10.70904/Keywords:
MSMEs, Artificial Intelligence (AI), Stock Management, Management Efficiency, AiStock ApplicationAbstract
SMEs play a crucial role in the Indonesian economy, yet face challenges in stock management, particularly in the digital retail sector. This research aimed to explore how AI-based technology could assist SMEs in managing stock efficiently through the development of the AiStock application. Employing a qualitative approach, this study collected data through interviews and observations with SME operators to understand the challenges faced in stock management and their reception towards new technology. The AiStock application was designed based on these findings, with key features such as demand forecasting, automatic notifications, and real-time analytical dashboards. The research findings demonstrated that this application enhanced SME stock management efficiency by reducing time spent on stock management, decreasing stockout frequency, and improving product availability. Users provided positive feedback regarding the ease of use of the application and the accuracy of predictions that assisted them in data-driven decision-making. This research concluded that the implementation of AI technology in SME stock management could improve operational efficiency and support competitiveness in the digital era. The AiStock application offered a relevant, practical, and affordable solution for SMEs in Indonesia to address managerial challenges and enhance their business sustainability.
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Copyright (c) 2025 Dr. Burhanudin, SE., MM, Alifina Azra (Author); Firda Nazhifah (Translator); Diva Indonesia (Author); Tiara Insani (Translator)
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