Data Mining Earthquake Prediction with Multivariate Adaptive Regression Splines and Peak Ground Acceleration

نویسندگان

چکیده

Earthquake research has not yielded promising results because earthquakes have uncertain data parameters, and one of the methods to overcome problem parameters is nonparametric method, namely Multivariate Adaptive Regression Splines (MARS). Sumbawa Island part territory Indonesia in position three active earth plates, so prone earthquake hazards. Therefore, this important do. This study aimed analyze hazard prediction on island by using MARS Peak Ground Acceleration (PGA) determine risk The method used was MARS, which two completed stages: Forward Stepwise Backward Stepwise. were based testing parameter analysis obtained a Mathematical model with 11 basis functions (BF) that contribute response variable, 1,2,3,4,5,7,9,11, do 6, 8, 10. predictor variables greatest influence 100% Epicenter Distance 73.8% Magnitude. conclusion highest PGA values areas most hazards Sumbawa, Mapin Kebak, Rea, Pulau Panjang, Saringi.

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ژورنال

عنوان ژورنال: Matrik: jurnal manajemen, teknik informatika, dan rekayasa komputer

سال: 2023

ISSN: ['2476-9843']

DOI: https://doi.org/10.30812/matrik.v22i3.3061