Clustering Dataset Titik Panas dengan Algoritme RDBC Menggunakan Web Framework Shiny pada Bahasa R.

Abstract

Indonesia has tropical forest that is quite extensive, but forest fires often occur resulting in great impact for Indonesia. Monitoring hotspots can be one of the forest fire disaster mitigation efforts. Each hotspot will be recorded on a dataset that can be processed to obtain information. This study aims to build a clustering web application on the hotspot data. This application uses the R programming language to implement Recursive Density Based Clustering (RDBC) algorithms using Shiny framework. Clustering is performed on hotspot data of the Kalimantan island and province of South Sumatra in 2002-2003 to find the pattern of spread of hotspots. The results obtained from the clustering process are evaluated using the Silhouette Coefficient. The SC value of this research is 0.2045354 for Kalimantan Island dataset and 0.232323 for South Sumatera Province dataset. The result is displayed in the form of web pages that can be accessed easily and can be referred for subsequent fire occurrence prediction.