Implementasi Metode Rough Set Dalam Memprediksi Dampak Tanah Longsor (Studi Kasus Badan Penanggulangan Bencana Daerah (BPBD) Provinsi Sumatera Utara

Abstract

Landslides are displacement of slope-forming material in the form of rocks, rubble, soil or material. In the Province of North Sumatra, landslides often occur and cause loss of life and material damage. These impacts can be minimized based on predictions of the initial symptoms of landslides such as rainfall, slope, topography, landslide types and so on. To reduce the impact of landslides, it is necessary to build an understanding based on technical knowledge and skills about the prediction of landslide impacts using data from existing landslide disasters. Data mining is a series of processes to explore the added value of a data set in the form of knowledge that has not been known manually. Data mining is very helpful in extracting information about the predicted impact of landslides in North Sumatra Province. The data mining method used is the Rough Set method. The Rough Set method is used to predict the impact of a landslide based on data on factors causing landslides and the area where landslides occur. Rough set is an efficient technique for Knowledge Discovery in Database (KDD) in the process stages and Data Mining.