Implementation of Data Mining to Predict The Feasibility of Blood Donors Using C4.5 Algorithm

Anita Febriani, Tiara Trimadya Rahmawati, Eka Sabna

Abstract


Blood Transfusion Unit PMI Pekanbaru City is part of a company or agency that serves blood donation, every blood bag obtained from the community voluntarily come to PMI to donate blood with the goal of humanity. In Blood Transfusion Unit PMI Pekanbaru City, has provisions to be blood donors that must be met in order to donate blood in UTD PMI Pekanbaru City. Data Mining is a combination of a number of computer science disciplines that are defined as the process of discovering new patterns from massive data sets. By using RapidMiner software and using the method of Decision Tree Algorithm C4.5 to determine the eligibility of blood donors based on Age, Weight, Hemoglobin, and Blood Pressure. In the study of hemoglobin is the most decisive variable in blood donors. And the result accuracy is 94.02% which means the accuracy of this model is very good.

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