Abstract
Indonesia is ranked 7th out of 10 countries with thehighest number of sufferers. BPJS Health include First LevelHealth Facilities (FKTP) and Advanced Referral HealthFacilities (FKRTL) which Type 2 diabetes mellitus is one ofthe ten most common diagnoses at FKRTL visits and ranksthird after follow-up examinations after treatment forconditions other than malignant neoplasms and kidney failurewith a percentage of 3.54% and a total of 62,455 for 2019 to2020. In deciding policies related to the funding of BPJSparticipants who suffer from diabetes mellitus, it is necessaryto have the characteristics of each region so that policy makingis more appropriate. The method used in this study usesclustering analysis using the K-means algorithm for typeII diabetes mellitus in Indonesia from 2015-2020 byprovince. Based on the outcome of the clusteringprovinces in indonesia using K-Means algorithm withoptimization of the determination of the number ofcluster using elbow method formed 3 cluster. 1 st cluster has21 province, the 2 nd cluster has 9 province and the 3 rd clusterhas 4 province.
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