Perbandingan Akurasi Metode Fuzzy Mamdani dan Fuzzy Sugeno dalam Memprediksi Kebutuhan Darah PMI Kota Medan - Putri, Vira Amalia; Sitepu, Suryati (Program Studi Pendidikan Matematika FKIP UNIVA Medan, 2024)
Blood demand prediction is important to avoid the instability of blood stocks or supplies. Too much and abundant blood stock can cause losses, because the blood will be wasted when it passes the storage expiration date. Meanwhile, too little stock can risk a shortage of blood supply. To anticipate this, it is necessary to predict the amount of blood demand that must be received in the future in order to achieve optimum blood availability. Fuzzy Mamdani and Fuzzy Sugeno methods that use the concept of fuzzy logic are considered capable of handling complexity and uncertainty in decision making, so they can be used to predict the amount of blood demand by considering the varying and uncertain amounts of blood demand and supply. The calculation results show that the Fuzzy Mamdani method has better accuracy than the Fuzzy Sugeno method with MAPE values of 16.707% and 17.987% respectively. The Fuzzy Mamdani method has an accuracy level in the good category according to the MAPE method and can be used to predict blood demand at PMI Medan.