Along with the times, the use of electricity is also increasing due to the use of electronic goods which are a necessity in this modern era which can be one of the factors that cause fires in the house, the factors for the occurrence of fires are natural factors, namely earthquakes, lightning strikes , volcanic eruptions, and drought, while the human factor itself is the installation of poor electrical installations at home can result in short circuits and cause fires, starting fires in places that are easy to trigger fires such as starting fires near fuel (gasoline) storage, using equipment cooking, and forgetting to unplug electronics when traveling. Therefore, in writing this thesis the title taken is Internet of Things-Based Fire Detection System to Prevent House Fires made using the Prototype Method, the system created is expected to help overcome or prevent fires in people's homes, as well as provide information to homeowners who is going to the smartphone owner of the house, and also sounds the fire alarm so that residents or residents around the house know that the house is on fire, so that residents can evacuate their belongings and can also help extinguish the fire in the house, because The density of housing or settlements in the city of Bekasi is very possible for the potential for fires to occur, and also to reduce the spread of Corona Virus 19 (Covid-19), this research was conducted at Wahana Harapan Housing Block D1 No.15.

One of the services at the posyandu is weighing toddlers. But sometimes there is still a lack of accuracy in the measurement results. Therefore, in this study, designed and realized something that can measure body weight and provide information accurately and connected to a database. The software development method used in this research is the prototype method which supports the stages of making a prototype product before it becomes the final result. This measuring tool uses Arduino Uno as a microcontroller board, loadcell sensor to measure weight, and RFID to detect toddler's self data. The data from the two sensors is processed by Arduino Uno to be input into the database, the toddler's weight will be displayed on the LCD and sensor data will be displayed on the monitoring website. The results of the blackbox test of this system indicate that the tool can function properly