Predicting Potential Blood Donors Who Can Attend Blood Donation Activities using a Support Vector Machine

Lack of blood will be fatal for the human body. Current technology has not been able to produce human blood, therefore blood donors from other people are needed. Because of this need, the Red Cross organized blood donation activities to obtain blood supplies. Blood donation is given by people voluntarily, therefore it is difficult to predict how much blood supply will be obtained in an organized blood donation activity. A system is needed to predict the number of potential donors so that the supply is sufficient. This study will classify potential blood donors and predict the number of blood donors who have the possibility to attend a blood donation activity held certain location at a certain time by using a support vector machine. With this prediction, the Red Cross can predict in advance how many bags of blood can be obtained before carrying out blood donation activities at a certain location at a certain time. In this way, the Red Cross will be able to find the right place and date to obtain maximum blood donation. The dataset used is data on blood donations carried out by donors at the Indonesian Red Cross in 2015 - 2019 with a total data of 53708 donors. From this study, it was found that the application made was able to classify potential donors and predict donors who could be present to give donors at a certain location and at a certain time with an F1 Score of 85%