Analisis Clustering Donor Darah dengan Metode Agglomerative Hierarchical Clustering
DOI:
https://doi.org/10.30865/resolusi.v3i6.977Keywords:
Clusteing; SEMMA; Agglomerative Hierarchical Clustering; Shilhouette CoefficientAbstract
Blood is a fluid that has the function of supplying nutrients, transporting metabolic products, sending oxygen and as natural antibodies to fight viruses or bacteria in the body. The Blood Donor Unit (UDD) of PMI (Indonesian Red Cross) is one of the agencies responsible for ensuring the availability of blood. To meet this availability, this agency carries out various programs, in an effort to ensure that the availability of blood is maintained. But in reality, there is a gap between supply and demand, where the need for blood is higher than the supply of blood. The problem of relatively high demand and a minimum number of blood donors can be used as a research topic, with the aim of producing information about the number of donors, blood types and availability, and temporary donor sites in each sub-district in Purwakarta district. This research will use the Agglomerative Hierarchical Clustering (AHC) algorithm, with the methodology used, namely SEMMA, the stages are: sample, explore, mpodify, model, and assess. The attributes used are id, district, blood group, latitude and longitude. From these attributes, clustering is made using the Agglomerative Hierarchical Clustering (AHC) algorithm using Orange, and visualized using Power BI. The research results from this data cluster get 3 clusters, the most donors are in Purwakarta District and followed by Bungursari District. Then the evaluation was assessed using the Silhouette Coefient which resulted in an accuracy rate of 0.713346292
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