Prediction of FKRTL Services Diagnosed with Type 2 Diabetes Mellitus Using the Hierarchical Agglomerative Clustering Time Series Method

Abstract

Diabetes Mellitus (DM) is a disease characterized by hyperglycemia or increased blood sugar levels and metabolic disorders. DM is a disease with a high prevalence rate in Indonesia. DM is included in the 10 most frequent Advanced Referral Health Facility (FKRTL) visits diagnoses. This research aims to find out provincial groupings based on data from FKRTL visits of participants diagnosed with T2DM using the Hierarchical Agglomerative Clustering method (single linkage, complete linkage, average linkage) and to find out predictions of participants diagnosed with T2DM at FKRTL visits using the Autoregressive Integrated Moving Average (ARIMA) method. The method used is Hierarchical Agglomerative Clustering Time Series. This research shows that the best algorithm is average linkage with a number of clusters of two. Forecasting provides a pattern that tends to decline.