Dadang Priyanto, DP and Bambang Krismono Triwijoyo, BK and Deny Jollyta, DJ and Hairani Hairani, HH and Ni Gusti Ayu Dasriani, NG (2023) Data Mining Earthquake Prediction with Multivariate AdaptiveRegression Splines and Peak Ground Acceleration. Data Mining Earthquake Prediction with Multivariate AdaptiveRegression Splines and Peak Ground Acceleration, 22 (3). pp. 583-592. ISSN 2476-9843

Preview	Text Bukti Pendukung.pdf Download (929kB) | Preview
Preview	Text Turnitin 13-Data_Mining_Earthquake_Prediction_With_Multivariat.pdf Download (2MB) | Preview

Abstract

Earthquake research has not yielded promising results because earthquakes have uncertain data param-eters, and one of the methods to overcome the problem of uncertain parameters is the nonparametricmethod, namely Multivariate Adaptive Regression Splines (MARS). Sumbawa Island is part of theterritory of Indonesia and is in the position of three active earth plates, so Sumbawa is prone to earth-quake hazards. Therefore, this research is important to do. This study aimed to analyze earthquakehazard prediction on the island of Sumbawa by using the nonparametric MARS and Peak GroundAcceleration (PGA) methods to determine the risk of earthquake hazards. The method used in thisstudy was MARS, which has two completed stages: Forward Stepwise and Backward Stepwise. Theresults of this study were based on testing and parameter analysis obtained a Mathematical model with11 basis functions (BF) that contribute to the response variable, namely (BF) 1,2,3,4,5,7,9,11, and thebasis functions do not contribute 6, 8, and 10. The predictor variables with the greatest influence were100% Epicenter Distance and 73.8% Magnitude. The conclusion of this study is based on the highestPGA values in the areas most prone to earthquake hazards in Sumbawa, namely Mapin Kebak, MapinRea, Pulau Panjang, and Pulau Saringi

Item Type:	Article
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Teknik dan Desain > Ilmu Komputer
Depositing User:	Dr. Dadang Priyanto, S.Kom.,M.Kom
Date Deposited:	09 Oct 2023 00:32
Last Modified:	09 Oct 2023 00:32
URI:	http://repository.universitasbumigora.ac.id/id/eprint/3410

Actions (login required)

View Item