Penerapan Metode Fuzzy Logic pada Early Warning System Keamanan Rumah Otomatis Berbasis IoT

Abstract

A large number of workers lost their jobs due to employee reductions in various companies caused by the economic crisis. Due to today's high levels of poverty, there is an increase in crime rates as well, especially theft and robbery, which are becoming more common in buildings such as apartment houses, dormitories and offices. Theft is a crime that can cause material loss and even human life, so it is necessary to apply IoT in an automatic home security system using the fuzzy logic method which is expected to help minimize the level of loss. This research tries to explore the application of the fuzzy logic method in improving the performance of early warning systems for automated home security. The fuzzy logic approach allows systems to cope with changing environmental conditions and complexity in a more adaptive manner than traditional methods. By utilizing sensors connected to the IoT network, information from the surrounding environment can be collected and analyzed in real-time using fuzzy rules. This research will consider factors such as movement, light, and pressure to determine the level of risk associated with potential home security intrusions. Based on this analysis, an early warning system can produce more accurate and responsive early warnings to security threats. Through experiments and simulations, this research will show the effectiveness of the fuzzy logic method in improving the performance of an IoT-based early warning system for automatic home security. The IoT implementation in the Early Warning System plan that was built can be used to send warning messages received by sensors to the Telegram chatbot. The results of this research significantly advance the creation of smarter, more adaptable home security systems.