Open AccessGIS implementation and classterization of potential blood donors using the agglomerative hierarchical clustering method
Author(s) -
Pratama Ryan Harnanda,
Natalia Damastuti,
Tresna Maulana Fahrudin
Publication year - 2021
Publication title -
ijeeit : international journal of electrical engineering and information technology
Language(s) - English
Resource type - Journals
eISSN - 2615-2088
pISSN - 2615-2096
DOI - 10.29138/ijeeit.v3i2.1305
Subject(s) - hierarchical clustering , cluster analysis , cluster (spacecraft) , silhouette , blood supply , geography , computer science , data mining , medicine , artificial intelligence , surgery , programming language
The blood needs of PMI (Indonesian Red Cross) in the Surabaya City area are sometimes erratic, the problem occurs because the amount of blood demand continues to increase while the blood supply is running low. As the main objective of this research, data mining was applied to able to cluster the blood donor data in UTD-PMI Surabaya City Center which was to determine both potential and no potential donors and also visualize the pattern of donor distribution in Geographic Information System (GIS). Agglomerative Hierarchical Clustering was applied to obtain the clustering result from the existing of 8757 donors. The experiment result shown that the cluster quality was quite good which reached 0.6065410 using Silhouette Coefficient. We concluded the one interesting analysis that private male employees with blood type O, and live in the eastern part of Surabaya City are the most potential donors.