MANAJEMEN PENGETAHUAN UNTUK RISIKO BENCANA TSUNAMI –LITERATURE REVIEW - Hadi Purwanto; Johan Danu Prasatya; Tedy Agung Cahyadi; Yohana Noradika Maharani (LPPM Universitas Abdurrab, 2022)
The application of knowledge management (KM) using Internet of Things (IoT) and Artificial Intelligence (AI) technology is able to capture, store, and disseminate disaster information in all phases of the tsunami disaster. IoT promises to provide continuous fast data, AI used in several disaster risk management applications promises to automate the analysis and dissemination of potential disaster information, as well as the results of disaster event analysis more accurately and faster. This study aims to develop an AI and IoT-based KM model for tsunami risk management based on the comparative results of previous research. The results of the comparison show that most KM, AI, and IoT research focus on the process of knowledge capture, knowledge store, knowledge sharing and mostly focus on pre-disaster. Some other KM research focuses on KM systems without AI, and IoT on the process of knowledge capture, knowledge store, knowledge sharing and only focuses on the stage of a disaster. There is very limited KM research that simultaneously examines KMS, AI, IoT in all knowledge management processes for all stages of tsunami disaster risk. The results of the comparison utilize to develop AI and IoT-based KM models for all stages of tsunami disaster risk management. This study can be a good guidance for stakeholders on the application of AI-based KM and IoT technology to manage tsunami disaster risk in Indonesia.