The Fuzzy Mamdani Implementation to Predict Blood Stock Needs in Blood Transfusion Unit of Palang Merah Indonesia (PMI) in Bandung District
Elis Ratna Wulan, Gitarja Sandi, Shahira, Muhammad Deden Firdaus, Yogi Saputra
UIN Sunan Gunung Djati Bandung
Abstract
Blood stock needs in blood transfusion unit of Palang Merah Indonesia in Bandung district are decreasing due to several things. To resolve this problem, a method to predict future blood stock needs is needed. With Fuzzy Mamdani method, the prediction results can be grouped into categories, those are stock in stock and fixed stock. Based on system testing and manual testing carried out in this study, it was found that Mamdani fuzy had a high enough level of accuracy of 88.88% to predict blood stock needs in Blood Transfusion Unit of Palang Merah Indonesia in Bandung district.
Keywords: Fuzzy, mamdani, transfusion, blood, predictions, stock
Topic: Computer Science