<![CDATA[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.]]>
Copyrights © 2025
