Prediksi Tsunami Pada Gempa Menggunakan Random Forest Classifier

  • Jerry Lasama Institut Teknologi Telkom Purwokerto
  • Andre Pradika E.P. Institut Teknologi Telkom Purwokerto
  • Agi Prasetiadi Institut Teknologi Telkom Purwokerto
Keywords: gempa, machine learning, random forest, tsunami

Abstract

Gempa yang diikuti oleh tsunami memiliki ciri khusus seperti kedalaman, besar, dan lokasi tertentu yang harus dianalisis terlebih dahulu sebelum dinyatakan akan diikuti tsunami atau tidak. Kemajuan teknologi machine learning memungkinkan kita melakukan prediksi terjadinya tsunami lebih efisien dibanding sebelumnya. Riset ini memanfaatkan machine learning khususnya algoritme Random Forest Classifier untuk membuat model yang dapat memprediksi potensi tsunami dengan
menggunakan data historis global significant earthquake milik NOAA dari tahun 2100 SM yang berisi pola Negara, Kode Region, Lintang, Bujur, Tahun, Bulan, Tanggal, Kedalaman, serta Besarnya gempa. Hasil simulasi model untuk memprediksi tsunami dari gempa pada testing set menunjukan akurasi di atas 75%.

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Published
2020-03-16
How to Cite
Lasama, J., E.P., A., & Prasetiadi, A. (2020). Prediksi Tsunami Pada Gempa Menggunakan Random Forest Classifier. Conference on Electrical Engineering, Telematics, Industrial Technology, and Creative Media (CENTIVE), 2(1), 39-47. Retrieved from http://conferences.ittelkom-pwt.ac.id/index.php/centive/article/view/85
Section
Articles