Time Series Clustering Analysis Using Dynamic Time Warping Technique of Daily Rainfall in Bengkulu Province
Herlin Fransiska, D Agustina, D Setyorini, I M Sumartajaya, Anang Kurnia · IOP Conference Series Earth and Environmental Science · 2024
Abstract Climate change is an important issue. The Meteorology, Climatology, and Geophysics Agency indicates that the state of climate change is critical. Climate change, such as high rainfall, can hurt people’s daily lives, causing floods, landslides, and other disasters. As a result, this researcher will use the time series clustering approach to analyze the mapping of rainfall in Bengkulu Province using data from 2001-2020. This work uses Dynamic Time Warping (DTW) and Euclidean to determine the similarity. The best is DTW. The results obtained show that in Bengkulu province, there are 2 clusters. The members of Cluster 1 have one rain station, and Cluster 2 has 14 rain stations. Cluster 1 is included in the low rainfall category. Cluster 2 is a cluster with a high rainfall category.