Memanfaatkan Motion Sensor untuk Pencegahan Pencurian Barang - Rafly Shaquille Subhan; I Gede Surya Rahayuda (Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University, 2023)
In response to escalating security concerns, this research investigates the potential of motion sensors as a cutting-edge technology for theft prevention. The study employs experimental and quantitative methods to evaluate the efficacy of motion sensors in diverse settings, focusing on the prevention of helmet theft, a significant issue in various regions. Utilizing Packet Tracer simulation, the implementation of motion sensors is explored, emphasizing factors such as placement, sensitivity settings, and effective monitoring. The findings demonstrate a substantial reduction in theft incidents, attributing this success to the swift detection of suspicious movements and prompt alerts to authorities. The research underscores the importance of proper usage and maintenance in maximizing the anti-theft capabilities of motion sensors. By simulating the implementation through Packet Tracer, the study not only leverages conceptual and theoretical aspects but also provides practical testing replicable and analyzable through simulations. The research aims to contribute valuable insights into the application of motion sensor technology for preventing helmet theft and encourages the widespread adoption of quality helmets for enhanced safety.