ANALISA PERBANDINGAN METODE FUZZY MAMDANI, SUGENO, DAN TSUKAMOTO DALAM PREDIKSI JUMLAH PENGADAAN OBAT
Daftar Isi:
- Fuzzy logic is one method for analyzing systems that contain uncertainty. In this study the Mamdani method, Ssugeno method, and Tsukamoto method was used to predict the amount of drug procurement. Prediction of the drug amount of procurement carried out by using three variables, namely sales, inventory and procurement. Variable sales consists of five fuzzy sets, namely: very down, down, normal, up, and very up, variable inventory consists of five fuzzy sets, namely: very little, little, normal, lot, and very lot, while procurement is made up of five variable fuzzy set, which very decreases, decreases, normal, increases, and very increases. By combining all these fuzzy sets, obtained 25 fuzzy rules, which is then used in each inference. Analysis using the Mamdani method, Sugeno method, Tsukamoto method on 100 drug data, produces Sugeno fuzzy that is has good forecasting capabilities, with MAPE value 10.633673%. MAPE Mamdani is 22,968618%, and Tsukamoto's MAPE is 12.306409%