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All Journal Journal of Data Mining and Information Systems
Beata Berlina Halawa
Universitas Katolik Santo Thomas Medan
Computer Science & IT

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Klasifikasi Gempa Bumi Menggunakan Algoritma Decision Tree Berbasis Data BMKG Dessianna Natalia Sembiring; Beata Berlina Halawa; Sardo P Sipayung
JDMIS: Journal of Data Mining and Information Systems Vol. 4 No. 1 (2026): February 2026
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v4i1.7118

Abstract

This study was conducted to classify earthquakes using the Decision Tree algorithm based on data from the Meteorology, Climatology, and Geophysics Agency. Indonesia is a region with high seismic activity, which requires a systematic classification method to group earthquakes according to their characteristics. The data used in this study consisted of earthquake magnitude and depth parameters, which were classified into light, moderate, and strong earthquake classes. The research stages included data collection, data preprocessing, determination of earthquake classes, construction of a classification model using the Decision Tree algorithm, and evaluation of the classification results. The results showed that the Decision Tree algorithm was able to classify earthquakes effectively based on the combination of magnitude and depth values. The resulting model generated clear and easily interpretable decision rules to distinguish between light, moderate, and strong earthquake classes. The conclusion of this study indicated that the Decision Tree algorithm could be used as an effective and interpretable method for earthquake classification based on data from the Meteorology, Climatology, and Geophysics Agency.
Co-Authors Dessianna Natalia Sembiring Sardo P Sipayung