Published: 2026-01-01

Pengaruh Optimasi Hyperparameter Random Forest terhadap Akurasi Prediksi Magnitudo Gempa Bumi Berdasarkan Hasil Klasterisasi DBSCAN

DOI: 10.35870/jtik.v10i1.5555

Rizky Dwi Prasetyo, Nadia Anissa Maori, Akhmad Khanif Zyen
  • Rizky Dwi Prasetyo: Universitas Islam Nahdlatul Ulama Jepara
  • Nadia Anissa Maori: Universitas Islam Nahdlatul Ulama Jepara
  • Akhmad Khanif Zyen: Universitas Islam Nahdlatul Ulama Jepara
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Abstract

Indonesia is a country with high seismic activity due to its location at the convergence of three major tectonic plates. This condition creates a strong need for earthquake pattern analysis and magnitude prediction to support disaster mitigation. This study aims to cluster earthquake data using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and to predict earthquake magnitude using the Random Forest algorithm optimized through hyperparameter tuning. The Indonesian earthquake dataset was obtained from Kaggle with a total of 92,887 valid entries. The DBSCAN clustering results revealed several active seismic zones, particularly in Sumatra, Java, Sulawesi, and Papua. The comparison of R² between the Baseline Random Forest and the Tuned Random Forest shows a significant improvement after the parameter tuning process. The Tuned Random Forest model achieves an R² value of 0.478, which is higher than the Baseline Random Forest's 0.442. This indicates that the tuned model is better able to explain the variance in the data and provides more accurate predictions.

Keywords

Earthquake ; DBSCAN ; Random Forest ; Magnitude Prediction ; Machine Learning ; Hyperparameter Tuning

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How to Cite

Prasetyo, R. D., Maori, N. A., & Zyen, A. K. (2026). Pengaruh Optimasi Hyperparameter Random Forest terhadap Akurasi Prediksi Magnitudo Gempa Bumi Berdasarkan Hasil Klasterisasi DBSCAN. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 10(1), 405-415. https://doi.org/10.35870/jtik.v10i1.5555
Article Information

This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.

  • Issue: Vol. 10 No. 3 (2026)

  • Section: Computer & Communication Science

  • Published: %750 %e, %2026

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Author Biographies
Rizky Dwi Prasetyo
Google Scholar ResearchGate ORCID

Program Studi Tekni Informatika, Fakultas Sains dan Teknologi, Universitas Islam Nahdlatul Ulama Jepara, Kota Jepara, Provinsi Jawa Tengah, Indonesia.

Nadia Anissa Maori
Google Scholar ResearchGate ORCID

Program Studi Tekni Informatika, Fakultas Sains dan Teknologi, Universitas Islam Nahdlatul Ulama Jepara, Kota Jepara, Provinsi Jawa Tengah, Indonesia.

Akhmad Khanif Zyen
Google Scholar ResearchGate ORCID

Program Studi Tekni Informatika, Fakultas Sains dan Teknologi, Universitas Islam Nahdlatul Ulama Jepara, Kota Jepara, Provinsi Jawa Tengah, Indonesia.

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