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International Journal of Artificial Intelligence Research
Published by STMIK Dharma Wacana
ISSN : -     EISSN : 25797298     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal Of Artificial Intelligence Research (IJAIR) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics of Artificial intelligent Research which covers four (4) majors areas of research that includes 1) Machine Learning and Soft Computing, 2) Data Mining & Big Data Analytics, 3) Computer Vision and Pattern Recognition, and 4) Automated reasoning. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.
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Articles 621 Documents
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IOT AND MACHINE LEARNING INTEGRATION TO PERSONALIZE SHOPPING EXPERIENCES IN SMART MALLS Fajri, Teuku Irfan
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1.1609

Abstract

The development of digital technology is driving significant transformation in the retail industry, one of which is through the application of the Internet of Things (IoT) and Machine Learning (ML) in smart mall management. This research aims to analyze how the integration of IoT and ML can create a more optimal personalized shopping experience for visitors. The method used is qualitative research with a literature review approach, namely reviewing various scientific studies, research reports, and academic publications related to IoT implementation, ML analytics, and personalization concepts in the context of smart retail. The study results show that IoT enables real-time customer data collection through sensors, beacons, mobile devices, and smart camera systems. The data is then processed using ML algorithms to produce personal recommendations, predictions of consumer preferences, visitor movement patterns, and automatic service adjustments. The integration of these two technologies is proven to improve the quality of the shopping experience through relevant offers, navigation efficiency, optimization of tenant management, and increased customer interaction with the mall environment. In addition, the literature shows that the success of smart malls depends on the quality of system integration, data security, privacy transparency, and the readiness of human resources in managing technology. This research concludes that the use of IoT and ML has great potential in forming a smart retail ecosystem that is responsive and customer-centered. However, implementation needs to pay attention to ethical, technical and operational challenges so that personalization can be achieved without reducing consumer comfort and trust. It is hoped that this study can become a conceptual basis for the development of further research and digital transformation strategies in the modern retail sector.

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