Backpropagation Neural Network for Determination of Mount Merapi Activities

Abstract

Monitoring of volcanic activity plays an important role in knowing changes in mountain activity. The discovery of anomalous data was the purpose of monitoring to determine whether there was a change in activity that indicates an eruption or vice versa. One of the monitoring activities carried out was periodic activity by measuring the distance of mountain body fracture with distance measurement (EDM). In this study, a combination of Neural Network Backpropagation method was proposed to detect anomalies in the monitoring data of Mount Merapi EDM. The experimental results showed an average accuracy of 97.3% in EDM of Mt. Merapi seismic activity.