EARLY WARNING TRAINING MODEL DEVELOPMENT EARTHQUAKE WITH INTERNET OF THINGS BASED ON SETS VALIDATION - Arfanda AS , Ambiyar, Rusnardi , Erwinsyah Simanungkalit , Fakhriza, (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
The goal of this research is to create an earthquake early warning training model using the internet of things (IoT) based on SETS (Science, Environment, Technologies, Social). The research began with the development of an IoT-based early warning tool that uses Android as a mode of public dissemination of earthquake events. When the application is finished, it is incorporated into the earthquake early warning training material, where the training model employs SETS. This training model aims to increase community preparedness and vigilance in order to save themselves when earthquake information is disseminated by the created application. The study's findings enabled the development of an earthquake early warning application called Ewae, as well as the training of the community using a SETS-based training model. The model development results in six new syntaxes: a) Organization and Orientation, b) Concept formation, c) Application introduction, d) Simulating applications, e) Disaster response, and f) Training evaluation. The Ewae application's output includes model books, instructor manuals, and participant handbooks.