ANALISIS KOMPARASI METODE TSUKAMOTO DAN SUGENO DALAM PREDIKSI JUMLAH SISWA BARU

  • Siti Abidah STMIK Banjarbaru
Keywords: prediction, new students, fuzzy logic, tsukamoto, sugeno

Abstract

The number of new students in the admission of students the new school year can be increased, and can also be decreased , it is a problem faced by SMK Telkom Sandhy Putra Banjarbaru in determining the strategic steps in the future so it is necessary to prediction or forecasting to know of the number of new students, so that all policies and decisions in planning ahead can be met properly .

                    In a study conducted analysis of two fuzzy inference system, the method Tsukamoto and Sugeno to determine which method is most accurate to be used to predict the number of new students the wave of the SMK Telkom Sandhy Putra Banjarbaru, where the results of such predictions can provide convenience to the parties SMK Telkom Sandhy Putra Banjarbaru in determining the strategic steps in decision-making and policy in two waves.

                Based on the research that has been done to predict the number of new students, Tsukamoto method produces accuracy rate of 90.41% with an average value afer a deviation occurs between the real data with data from the prediction of 9.59%. And Sugeno method has an accuracy rate of 85.92% with a value afer that occurs between real data with the data predicted by 14.08%, so that the resulting analysis showed that Tsukamoto method has a higher degree of accuracy than the Sugeno method.
Section
Articles