Implementasi Business Intelligence Menggunakan ETL dan K-MEANS untuk Visualisasi Data Bencana Alam di Jawa Barat - Firmansyah, Devie; Ramdani, Deni; Dongoran, Awaluddin; Januriana, Andi Moch (INTERNAL (Information System Journal), 2024)
In addition to its abundant natural wealth, West Java also harbors a high potential for disasters. The increasing frequency of natural disasters in recent years, such as earthquakes, landslides, and floods, has caused significant losses to the community. Climate change and environmentally unfriendly human activities are the main factors causing these disasters. Therefore, mitigation and preparedness efforts are key in facing future disaster threats. Business Intelligence can be used to process data and provide relevant information, which is a part of information technology. The purpose of this research is to visualize areas affected by natural disasters in West Java Province by implementing Business Intelligence. The method of this research is obtained in the form of a dataset sourced from the West Java Provincial Community and Village Empowerment Office, obtained through https://opendata.jabarprov.go.id/id for the period from 2020 to 2022. In this research, ETL (Extract, Transform, Load) is used to handle data, including extraction (Extract), transformation (Transform), and loading (Load), as well as K-Means calculations to cluster regions based on clusters. The result of this research is in the form of a dashboard report with the help of Google Data Studio, displaying data visualization results for the West Java region affected by natural disasters. Based on the visualization results, the areas in West Java Province with a high risk of natural disasters that fall into the first cluster in 2020 had 2 regions, in 2021 had 4 regions, and in 2022 had only 1 region.