Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal ICONESTH
Paramitha Nerisafitra
Teknik Informatika, Universitas Negeri Surabaya
Arts Humanities Computer Science & IT Dentistry Mathematics Neuroscience Nursing Public Health Social Sciences Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
PROBABILISTIC NEURAL NETWORK FOR ANOMALY DETECTION IN MOUNT MERAPI'S SEISMIC ACTIVITY: PERFORMANCE EVALUATION AND INSIGHTS Paramitha Nerisafitra; Tri Deviasari Wulan; Ricky Eka Putra; I Made Suartana
International Conference on Education, Science, Technology and Health (ICONESTH) 2024: The 2nd ICONESTH
Publisher : International Conference on Education, Science, Technology and Health (ICONESTH)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research aims to evaluate the performance of the Probabilistic Neural Network (PNN) method for detecting seismic anomalies in the monitoring data of Mount Merapi. The study utilized a dataset comprising 368 records, representing both normal activity and increased seismic activity. The dataset was divided into 70% for training and 30% for testing. During the training phase, the PNN model achieved an accuracy of 87%, indicating its capability to identify patterns in the seismic data effectively. However, the testing phase, conducted to validate the model’s generalization ability, yielded an accuracy of 64%. These results suggest that while the PNN method demonstrates promise in detecting seismic anomalies, its performance requires further improvement to enhance reliability in operational volcanic monitoring systems. Keywords: probabilistic neural network, seismic, performance
Co-Authors I Made Suartana Ricky Eka Putra Tri Deviasari Wulan