Abstract
Clustering is the stage that is carried out before further data analysis. There are many approach method that can be used for clustering time series data, one of which is the model-based approach. In this study, we clustering inflation data used the ARIMA model. The cluster model is carried out after obtaining the clusters. The similarity between time series is measured using the development of Piccolo distance. Furthermore, the Ward hierarchical method is used for clustering. The Silhouette averaging method is used to determine the optimal number of clusters. The cluster model can be used to represent individual models. The cluster model is more effective than creating all individual models.
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