NNTesting.m

%===========================================================================
% Program Pengujian MLP
% Variable yang dapat di update
% 1. JHneuron
% 2. Learning Rate
% 3. Epoch
% 4. MaxMSE
%===========================================================================

clc;
clear;

%===========================================================================
% Load hasil pelatihan dari file NNTraining.m
%===========================================================================

NNTraining

TestSet = ...
    [3 3 1;
    3 1 2;
    2 3 1;
    2 1 2;
    1 3 1;
    1 2 2;
    1 1 1;];
    
 TestKelas = [0 1 0 1 0 1 0];
     
JumPola = length(TestSet(:,1))  ;
JumBenar = 0;             

for pp=1:JumPola,
    CP = TestSet(pp,:);                 
         
    A1 = [];
    for ii=1:JHneuron,
        v = CP * W1(:,ii);
        A1 = [A1 1/(1+exp(-v))];
    end
    
    A2 = [];
    for jj=1:JOneuron,
        v = A1 * W2(:,jj);
        A2 = [A2 1/(1+exp(-v))];
    end
    
    A3(pp) = A2;
    
    %----------------------------------------------------------------------
    % Pemetaan A2 menjadi kelas keputusan
    % Jika A2 < 0.5 maka kelas = 0
    %----------------------------------------------------------------------      

    for jj=1:JOneuron,
      if A2(jj) < 0.5,
        Kelas = 0;
      else
        Kelas = 1;
      end
    end 
    
    if Kelas == TestKelas(pp),
      JumBenar = JumBenar + 1;
    end
       
 end
 
 JumBenar
 JumPola 
 display(['Akurasi JST = ' num2str((JumBenar/JumPola)*100) ' %']);