DENTIFICATION OF VOLCANIC EARTHQUAKE TYPES BASED ON SEISMIC RECORDING DATA FROM MOUNT SINABUNG USING PRINCIPAL COMPONENT ANALYSIS: IDENTIFIKASI JENIS GEMPA VULKANIK BERDASARKAN DATA REKAMAN SEISMIK PADA GUNUNG SINABUNG MENGGUNAKAN PRINCIPAL COMPONENT ANALYSIS - Bagas Anwar Arif Nur; Bambang Heru Iswanto; Mohammad Hasib; Ahmad Basuki (Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI, 2025)
Volcanic eruptions are natural events that have the potential for significant damage to humans and the environment. Identifying the type of volcano earthquake is key in disaster risk mitigation by providing information on the process and the location of magma activity beneath the volcano. In this research, we propose an approach using Principal Component Analysis (PCA) to identify types of volcanic earthquakes based on seismic recording data. Identification begins by reducing feature dimensions using Principal Component Analysis (PCA). The PCA results were then clustered and then evaluated Silhoutte Score, ARI, CH-Indeks, DB-Indeks. Experiments were carried out using recorded data totaling 329 samples. For each recording, feature extraction was carried out in the form of statistical features, entropy features and shape features with a total of 16 features in the time and frequency domains. PCA results on the two main components PC1 explained 49.2741% and PC2 24.5507% of the data variance and evaluation results using Silhouette Score were equal to 0.53, ARI 0.8, CH-Index 529.34, and DB- Index 0.6