Penuntun Praktikum Jaringan Syaraf Tiruan Dengan Matlab GUI IGA Widagda Fisika FMIPA UNUD 2014

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Penuntun Praktikum

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IGA Widagda

Fisika FMIPA UNUD

2014

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JST Hebb

1.1 Program Aplikasi Komputer JST Hebb

1.1.1.Rancangan Graphical User Interface (GUI)

1.1.2 Daftar Komponen

No

Komponen

Properti

1 Panel

title

Training

2 Axes

Tag

axes1

3 Axes

Tag

axes2

4 Axes

Tag

axes6

5 Axes

Tag

axes7

6 Axes

Tag

axes8

7 Push button

String

open image 1

Tag

image1_pushbutton

8 Push button

String

open image 2

Tag

image2_pushbutton

9 Push button

String

open image 3

Tag

image3_pushbutton

10 Push button

String

open image 4

Tag

image4_pushbutton

11 Push button

String

open image 5

Tag

image5_pushbutton

1

Gambar 1.1 Rancangan GUI program aplikasi JST Hebb

(3)

1.1.3. Kode Program (source code)

1.1.3.1 Function

image1_pushbutton

_Callback

function image1_pushbutton_Callback(hObject, eventdata, handles) [filename,pathname]=uigetfile('*.jpg;*.bmp;*.png','pilih gambar anda');

handles.image_file = strcat(pathname,filename); %"handles.image_file" var image_file %di set agar bisa diakses dari function

%yang lain

if exist(handles.image_file) % check if image exists

handles.im_original1=imread(handles.image_file); % read in the image axes(handles.axes1); % will display on axes1

imshow(handles.im_original1); else % if image doesn_t exist

imshow('file_not_found.jpg') % Display the _Error image_ end

guidata(hObject,handles);

1.1.3.2 Function

image2_pushbutton

_Callback

%yang lain

No

Komponen

Properti

12 Static text

String

Bobot (w) dan Bias (b) hasil training

13 List box

String

kosong

Tag

Show_listbox

14 Push button

String

start training

Tag

start_training

15 Panel

Title

Testing

16 Axes

Tag

axes3

17 Axes

Tag

axes4

18 Push button

String

open testing image

Tag

image_testing_pushbutton

19 Push button

String

Start testing

Tag

start_testing_pushbutton

20 Static text

String

Hasil Testing

(4)

1.1.3.3 Function

image3_pushbutton

_Callback

%yang lain

1.1.3.4 Function

image4_pushbutton

_Callback

%yang lain

1.1.3.3 Function

image5_pushbutton

_Callback

%yang lain

1.1.3.4 Function

start_training_pushbutton

_Callback

function start_training_pushbutton_Callback(hObject, eventdata, handles) s1=rgb2gray(handles.im_original1); s2=rgb2gray(handles.im_original2); s3=rgb2gray(handles.im_original3); s4=rgb2gray(handles.im_original4); s5=rgb2gray(handles.im_original5);

%ubah data menjadi bipolar[1,-1] jml_baris=size(s1,1);

(5)

for i=1:1:jml_baris for j=1:1:jml_kolom if s1(i,j)>=200 %putih s1_temp(i,j)=-1; else %hitam s1_temp(i,j)=1; end end end for i=1:1:jml_baris for j=1:1:jml_kolom if s2(i,j)>=200 %putih s2_temp(i,j)=-1; else %hitam s2_temp(i,j)=1; end end end for i=1:1:jml_baris for j=1:1:jml_kolom if s3(i,j)>=200 %putih s3_temp(i,j)=-1; else %hitam s3_temp(i,j)=1; end end end for i=1:1:jml_baris for j=1:1:jml_kolom if s4(i,j)>=200 %putih s4_temp(i,j)=-1; else %hitam s4_temp(i,j)=1; end end end for i=1:1:jml_baris for j=1:1:jml_kolom if s5(i,j)>=200 %putih s5_temp(i,j)=-1; else %hitam s5_temp(i,j)=1; end end end %jml_pola= 5; % 5 citra

%ubah matrik jadi jadi matrik kovektor k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; s(1,k)=s1_temp(i,j); end end

t1=1; %target untuk citra 1 simpan sbg 3 kolom %akhir dalam array s

t2=1; t3=1;

(6)

s(1,k+1)=t1; s(1,k+2)=t2; s(1,k+3)=t3; k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; s(2,k)=s2_temp(i,j); end end t1=1;

t2=1; %target untuk citra 2 t3=-1; s(2,k+1) = t1; s(2,k+2)= t2; s(2,k+3)=t3; k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; s(3,k)=s3_temp(i,j); end end

t1=1; %target untuk citra 3 t2=-1; t3=1; s(3,k+1) = t1; s(3,k+2) = t2; s(3,k+3)= t3; k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; s(4,k)=s4_temp(i,j); end end

t1=1; %target untuk citra 4 t2=-1; t3=-1 s(4,k+1) = t1; s(4,k+2) = t2; s(4,k+3)= t3; k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; s(5,k)=s5_temp(i,j); end end

t1=-1; %target untuk citra 5 t2= 1; t3= 1; s(5,k+1) = t1; s(5,k+2) = t2; s(5,k+3) = t3;

%inisialisasi bobot (w) dan bias (b) jml_pola=size(s,1);

(7)

jml_input = size(s,2)-3; %-3 krn output/target ada 3 jml_output=3;

%inisialisasi botot w dan bias b for j=1:1:jml_output for i=1:1:jml_input w(i,j)=0; end end for j=1:1:jml_output b(j)=0; end for n=1:1:jml_pola for i=1:1:jml_input

x(i) = s(n,i); %%x(i) = s(i) end for j=1:1:jml_output t(n,j)=s(n,jml_input+j); %target t % t(n,2)=s(n,jml_input+2); %target t y(n,j)=t(n,j); % y1 % y(n,2)=t(n,2); % y2 end

%perbaiki bobot dan bias for j=1:1:jml_output for i=1:1:jml_input

w(i,j) = w(i,j) + x(i)*y(n,j); % w_baru =w_lama+x(i)* y handles.w_final(i,j)=w(i,j);

end

b(j)=b(j)+y(n,j); %b_baru= b_lama + y handles.b_final(j)=b(j);

end end

%%tampilkan bobot dan bias hasil pelatihan di command window for i=1:1:jml_input for j=1:1:jml_output disp(strcat('w',num2str(i),num2str(j),' = ',num2str(w(i,j)))); end end for j=1:1:jml_output disp(strcat('b',num2str(j),' = ',num2str(b(j)))); end

%Tampilkan bobot dalam list box n=1;

for i=1:1:jml_input %index dari array bobot w for j=1:1:jml_output

k(n)=str2num(strcat(num2str(i),num2str(j))); w_vek(n)=w(i,j); %ubah w jadi vektor w_vek n=n+1;

end end

%tampilkan bobot bj, sbg elemen terakhir listbox set(handles.show_listbox,'String',strcat('w',num2str(k'),' = ',num2str(w_vek'))); for j=1:1:jml_output bobot=strcat('b',num2str(j),' = ',num2str(b(j))); list_box_old=cellstr(get(handles.show_listbox,'String')); list_box_new= [list_box_old;{bobot}]; set(handles.show_listbox,'String',list_box_new) ;

(8)

end

1.1.3.5 Function

image_testing_pushbutton

_Callback

function image_testing_pushbutton_Callback(hObject, eventdata, handles) [filename,pathname]=uigetfile('*.jpg;*.bmp;*.png','Select an Image File');

%yang lain

handles.im_testing=imread(handles.image_file); % read in the image axes(handles.axes3); % will display on axes1

imshow(handles.im_testing); else % if image doesn_t exist

1.1.3.6 Function

start_testing_pushbutton

_Callback

function start_testing_pushbutton_Callback(hObject, eventdata, handles) s=rgb2gray(handles.im_testing);

%ubah data menjadi bipolar[1,-1] jml_baris=size(s,1); jml_kolom=size(s,2); for i=1:1:jml_baris for j=1:1:jml_kolom if s(i,j)>=200 %putih s_temp(i,j)=-1; else %hitam s_temp(i,j)=1; end end end

%ubah matrik citra 2 dimensi s_temp jadi vektor 1 dimensi s k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; s_vektor(k)=s_temp(i,j); end end jml_input = k; jml_output =3; net(1)=0; net(2)=0; net(3)=0; for j=1:1:jml_output for i=1:1:jml_input x(i)=s_vektor(i); net(j)=net(j)+x(i)*handles.w_final(i,j); end net(j)=net(j)+handles.b_final(j); end axes(handles.axes4);

(9)

imshow(handles.im_original1); else

if net(1)>=0 && net(2)>=0 && net(3)<0 imshow(handles.im_original2); else

if net(1)>=0 && net(2)<0 && net(3) >=0 imshow(handles.im_original3); else

if net(1)>=0 && net(2)<0 && net(3) <0 imshow(handles.im_original4); else

if net(1)<0 && net(2)>=0 && net(3) >=0 imshow(handles.im_original5); else imshow(handles.im_original5); end end end end end

1.1.4 Hasil Eksekusi (RUN) program

Hasil eksekusi program JST Hebb dapat dilihat dalam Gambar 1.2.

Cara kerja program :

- Buka file citra atau gambar dengan menekan tombol

open image 1

sampai

open

image 5

- Klik tombol Start Training, setelah menunggu beberapa saat sistem akan

menampilkan bobot (w) dan bias (b) hasil pelatihan list box

- Buka file citra atau gambar dengan menekan tombol open testing image

- Klik tombol Start Testing, selanjutnya akan ditampilkan citra hasil testing yang

cocok dengan citra yang diuji.

(10)

2.1 Program Aplikasi Komputer JST Hebb (model 2)

2.1.1.Rancangan Graphical User Interface (GUI)

2.1.2 Daftar Komponen

No

Komponen

Properti

1 Panel

Title

Training

2 Axes

Tag

axes1

3 Axes

Tag

axes2

4 Axes

Tag

axes3

5 Push button

String

open

Tag

image1_pushbutton

6 Push button

String

<

Tag

before_pushbutton

7 Push button

String

>

Tag

next_pushbutton

8 Push button

String

Start Training

Tag

start_trainning_pushbutton

9 Push button

String

open

Tag

image_testing_pushbutton

10 Push button

String

Start Testing

Tag

start_testing_pushbutton

(11)

2.1.3. Kode Program (source code)

2.1.3.1 Function

image1_pushbutton

_Callback

function image1_pushbutton_Callback(hObject, eventdata, handles) current_dir=pwd; %getting current directory

handles.img_dir=uigetdir(current_dir,'Select directory'); %Selecting directory %where image saved

%Reading image files at one folder if exist(handles.img_dir)

cd(handles.img_dir); %change directory D = dir('*.jpg'); %list all image-file in directory

handles.img_original = cell(1,numel(D));%create 1 X numel(D) cell array of empty matrices

% numel(D)=number of element in directory D for i = 1:numel(D)

[handles.img_original{i},handles.fs{i}] = imread(D(i).name); %save into array 'img_original' end axes(handles.axes1); for i=1:numel(D) imshow(handles.img_original{i}); end handles.number_of_image=numel(D); handles.number_of_max=numel(D); else

h=msgbox('File not found', 'Warning','error'); end

cd(current_dir);%return into current directory

2.1.3.2 Function

before_pushbutton

_Callback

function before_pushbutton_Callback(hObject, eventdata, handles) axes(handles.axes1); % will display on axes1

i=handles.number_of_image; if i==1 % before_pushbutton.Enable='off'; imshow(handles.img_original{1}); %handles.number_of_img=1; else imshow(handles.img_original{i}); handles.number_of_image = handles.number_of_image-1;

No

Komponen

Properti

11 Static text

String

Database Citra

12 Static text2

String

Weight (w) dan Bias (b)

13 List box

String

kosong

Tag

show_listbox

14 Panel

Title

Testing

25 Static text

String

Hasil Testing

(12)

end

2.1.3.3 Function

next_pushbutton

_Callback

function next_pushbutton_Callback(hObject, eventdata, handles) axes(handles.axes1); % will display on axes1

i=handles.number_of_image; if i == handles.number_of_max imshow(handles.img_original{i}); else imshow(handles.img_original{i}); handles.number_of_image = handles.number_of_image+1; end guidata(hObject,handles);

2.1.3.4 Function

start_trainning_pushbutton

_Callback

function start_trainning_pushbutton_Callback(hObject, eventdata, handles) num_wav=size(handles.img_original,2); %number of wav files

for i=1:1:num_wav s(i,:,:)=rgb2gray(handles.img_original{i}); end jml_citra=size(s,1); jml_baris=size(s,2) jml_kolom=size(s,3)

%ubah citra asli bw menjadi bipolar[1,-1] for k=1:1:jml_citra for i=1:1:jml_baris for j=1:1:jml_kolom if s(k,i,j)>200 %putih s_temp(k,i,j)=-1; else %hitam s_temp(k,i,j)=1; end end end end

%ubah citra 'source' format matrik baris kolom(i,j) jadi format baris %citra 1 for m=1:1:jml_citra k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; s(m,k)=s_temp(m,i,j); end end end jml_input=k

%tentukan matrik target

handles.jml_target = 3; % 2^handles.jml_target jml_digit=handles.jml_target;

(13)

i=2^handles.jml_target-1; for k=1:num_wav

x=de2bi(i,jml_digit); %desimal to biner, tampilkan sebanyak 'jumlah digit' handles.target(k,:)=x;

i=i-1; end

%ubah target menjadi bipolar for k=1:num_wav for i=1:jml_digit if handles.target(k,i)==0 handles.target(k,i)=1; else handles.target(k,i)=-1; end end end

%inisialisasi bobot (w) dan bias (b) jml_pola=size(s,1)

%jml_input = size(s,2)

jml_output=handles.jml_target; %inisialisasi botot w dan bias b for j=1:1:jml_output for i=1:1:jml_input w(i,j)=0; end end for j=1:1:jml_output b(j)=0; end for n=1:1:jml_pola for i=1:1:jml_input

x(i) = s(n,i); %%x(i) = s(i) end for j=1:1:jml_output %t(n,j)=s(n,jml_input+j); %target t % t(n,2)=s(n,jml_input+2); %target t y(n,j)=handles.target(n,j); % y1 % y(n,2)=t(n,2); % y2 end

%perbaiki bobot dan bias for j=1:1:jml_output for i=1:1:jml_input

w(i,j) = w(i,j) + x(i)*y(n,j); % w_baru =w_lama+x(i)* y handles.w_final(i,j)=w(i,j);

end

b(j)=b(j)+y(n,j); %b_baru= b_lama + y handles.b_final(j)=b(j);

end end

(14)

%tampilkan bobot bj, sbg elemen terakhir listbox

set(handles.show_listbox,'String',strcat('w',num2str(k'),' = ',num2str(w_vek'))); for j=1:1:jml_output bobot=strcat('b',num2str(j),' = ',num2str(b(j))); list_box_old=cellstr(get(handles.show_listbox,'String')); list_box_new= [list_box_old;{bobot}]; set(handles.show_listbox,'String',list_box_new) ; end guidata(hObject,handles);

2.1.3.3 Function

_Callback

function image_testing_pushbutton_Callback(hObject, eventdata, handles) [filename,pathname]=uigetfile('*.jpg','Pilih file citra(*.jpg)');

handles.img_file = strcat(pathname,filename); if exist(handles.img_file) % check if image exists axes(handles.axes2); % will display on axes1

handles.img_testing=imread(strcat(pathname,filename)); %read image imshow(handles.img_testing);

else % if image doesn_t exist

h=msgbox('file not found', 'Error','error'); end

handles.pathname=pathname; handles.filename=filename; guidata(hObject,handles);

2.1.3.4 Function

_Callback

function start_testing_pushbutton_Callback(hObject, eventdata, handles) s=rgb2gray(handles.img_testing);

%ubah data menjadi bipolar[1,-1] jml_baris=size(s,1); jml_kolom=size(s,2); for i=1:1:jml_baris for j=1:1:jml_kolom if s(i,j)>200 %putih s_temp(i,j)=-1; else %hitam s_temp(i,j)=1; end end end s_temp

%ubah matrik citra baris-kolom s_temp jadi matrik baris k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; s_vektor(k)=s_temp(i,j); end end jml_input = k jml_output=handles.jml_target for i=1:jml_output net(i)=0; end size(handles.w_final) for j=1:1:jml_output

(15)

for i=1:1:jml_input x(i)=s_vektor(i); net(j)=net(j)+x(i)*handles.w_final(i,j); end net(j)=net(j)+handles.b_final(j) end for i=1:jml_output if net(i)>=0 net(i)=1 else net(i)=-1 end end jml_pola=size(handles.target,1); cocok=0; axes(handles.axes3); for i=1:jml_pola if handles.target(i,:)==net() imshow(handles.img_original{i}); cocok=1; handles.wav_hasil=strcat('wav',num2str(i),'.wav'); break; end end if cocok==0

h=msgbox('Tidak ada yang cocok','warning'); end

2.1.4 Hasil Eksekusi (RUN) program

Hasil eksekusi program JST Hebb dapat dilihat dalam Gambar 1.4.

Cara kerja program :

- Buka file citra atau gambar dengan menekan tombol

open

pada panel training

(16)

- Klik tombol Start Training, setelah menunggu beberapa saat sistem akan

menampilkan bobot (w) dan bias (b) hasil pelatihan pada list box

- Buka file citra atau gambar dengan menekan tombol open pada panel testing

- Klik tombol Start Testing, selanjutnya akan ditampilkan citra hasil testing yang

cocok dengan citra yang diuji.

3. Latihan

1. Buatlah percobaan dengan menggunakan program aplikasi JST Hebb model 2

dengan 5 buah citra pola huruf untuk proses pelatihan. Selanjutnya ujilah atau

testing sistem dengan citra huruf yang cacat atau mengandung noise.

2. Buatlah percobaan dengan memakai program aplikasi JST Hebb model 2 dengan

5 buah citra wajah untuk proses pelatihan atau training. Kemudian testing system

dengan citra wajah cacat atau mengandung noise

(17)

JST Perceptron

2.1.Rancangan Graphical User Interface (GUI)

1 ₂

1 ₁

(18)

2.2 Daftar Komponen

No

Komponen

Properti

1 Panel

Title

Training

2 Axes

Tag

axes1

3 Axes

Tag

axes2

4 Axes

Tag

axes3

5 Push button

String

open

Tag

image1_pushbutton

6 Push button

String

<

Tag

before_pushbutton

7 Push button

String

>

Tag

next_pushbutton

8 Push button

String

Start Training

Tag

start_trainning_pushbutton

9 Push button

String

open

10 Static text1

String

Alpha

11 Static text2

String

Tetha

12 Edit text1

String

kosong

Tag

alpha_edit

13 Edit text2

String

kosong

Tag

tetha_edit

14 Push button

String

Open testing image

Tag

image_testing_pushbutton

10 Push button

String

Start Testing

(19)

2.3. Kode Program (source code)

2.3.1 Function

image1_pushbutton

_Callback

current_dir=pwd; %getting current directory

handles.img_dir=uigetdir(current_dir,'Select directory'); %Selecting directory %where image saved

%Reading wav files at one folder if exist(handles.img_dir)

cd(handles.img_dir); %change directory D = dir('*.jpg'); %list all wav-file in directory

handles.img_original = cell(1,numel(D));%create 1 X numel(D) cell array of empty matrices

% numel(D)=number of element in directory D for i = 1:numel(D)

[handles.img_original{i},handles.fs{i}] = imread(D(i).name); %save into array 'img_original' end axes(handles.axes1); for i=1:numel(D) imshow(handles.img_original{i}); end handles.number_of_image=numel(D); handles.number_of_max=numel(D); else

h=msgbox('File not found', 'Warning','error'); end

2.3.2 Function

before_pushbutton

_Callback

axes(handles.axes1); % will display on axes1 i=handles.number_of_image; if i==1 % before_pushbutton.Enable='off'; imshow(handles.img_original{1}); %handles.number_of_img=1; else imshow(handles.img_original{i});

No

Komponen

Properti

12 Static text3

String

Weight (w) dan Bias (b)

13 List box

String

kosong

Tag

show_listbox

14 Panel

Title

Testing

25 Static text4

String

Hasil Testing

(20)

handles.number_of_image = handles.number_of_image-1; end

2.3.3 Function

next_pushbutton

_Callback

function next_pushbutton_Callback(hObject, eventdata, handles) axes(handles.axes1); % will display on axes1

i=handles.number_of_image; if i == handles.number_of_max imshow(handles.img_original{i}); else imshow(handles.img_original{i}); handles.number_of_image = handles.number_of_image+1; end guidata(hObject,handles);

2.3.4 Function

_Callback

num_file=size(handles.img_original,2); %number of files for i=1:1:num_file s(i,:,:)=rgb2gray(handles.img_original{i}); end jml_citra=size(s,1); jml_baris=size(s,2) jml_kolom=size(s,3)

%ubah citra 'source' format matrik baris kolom(i,j) jadi format baris(vektor) for m=1:1:jml_citra k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; s(m,k)=s_temp(m,i,j); end end end jml_input=k

%tentukan matrik target

handles.jml_target = 3; % 2^handles.jml_target jml_digit=handles.jml_target;

m=0;

i=2^handles.jml_target-1; for k=1:num_file

x=de2bi(i,jml_digit); %desimal to biner, tampilkan sebanyak 'jumlah digit' handles.target(k,:)=x;

(21)

i=i-1; end

%ubah target menjadi bipolar for k=1:num_file for i=1:jml_digit if handles.target(k,i)==0 handles.target(k,i)=1; else handles.target(k,i)=-1; end end end

alpha=str2num(get(handles.alpha_edit,'String')); %learning rate tetha=str2num(get(handles.tetha_edit,'String')); %threshold %inisialisasi bobot (w) dan bias (b)

jml_pola=size(s,1) %jml_input = size(s,2)

jml_output=handles.jml_target; %inisialisasi botot w dan bias b for j=1:1:jml_output for i=1:1:jml_input w(i,j)=0; end end for j=1:1:jml_output b(j)=0; end berhenti = false; jml_iterasi = 0; while berhenti==false jml_iterasi=jml_iterasi+1; berhenti=true; for n=1:1:jml_pola for i=1:1:jml_input x(i) = s(n,i); %x(i) = s(i) end %t(n)=s(n,jml_input+1); %target %y(n,j)=handles.target(n,j); % y1 for j=1:1:jml_output %t(n,j)=s(n,jml_input+j); %target t % t(n,2)=s(n,jml_input+2); %target t t(n,j)=handles.target(n,j); % y1 % y(n,2)=t(n,2); % y2 end % sigma=0; for j=1:1:jml_output sigma=0; for i=1:1:jml_input sigma=sigma+x(i)*w(i,j); end y_in(j)=b(j)+sigma; if y_in(j)>tetha y(j)=1; end

(22)

if y_in(j)>=-tetha && y_in(j)<=tetha y(j)=0; end if y_in(j)<-tetha y(j)=-1; end

%jika output(y) tidak sesuai target(t) maka perbaiki %bobot w dan bias b

if y(j) ~= t(n,j) for j=1:1:jml_output for i=1:1:jml_input w(i,j)=w(i,j)+alpha*t(n,j)*x(i); handles.w_final(i,j)=w(i,j); end b(j)=b(j)+alpha*t(n,j); handles.b_final(j)=b(j); berhenti=false; end end end end end

%%tampilkan bobot dan bias hasil pelatihan dalam command window editor for j=1:1:jml_output for i=1:1:jml_input disp(strcat('w',num2str(i),num2str(j),' = ',num2str(w(i,j)))); end disp(strcat('b = ',num2str(b(j)))); end

for n=1:1:jml_input %index dari array bobot w i(n)=n;

end

end end

set(handles.show_listbox,'String',strcat('w',num2str(k'),' = ',num2str(w_vek'))); %tampilkan bobot bj, sbg elemen terakhir listbox

for j=1:1:jml_output bobot=strcat('b',num2str(j),' = ',num2str(b(j))); list_box_old=cellstr(get(handles.show_listbox,'String')); list_box_new= [list_box_old;{bobot}]; set(handles.show_listbox,'String',list_box_new) ; end

j_iterasi=strcat('jml iterasi = ',num2str(jml_iterasi)); %tampilkan jumlah iterasi sbg elemen terakhir listbox list_box_old=cellstr(get(handles.show_listbox,'String')); list_box_new= [list_box_old;{j_iterasi}];

set(handles.show_listbox,'String',list_box_new) ; guidata(hObject,handles);

(23)

2.3.5 Function

_Callback

%yang lain

imshow(handles.im_testing); else % if image doesn t exist

imshow('file_not_found.jpg') % Display the Error image end

2.3.6 Function

_Callback

function start_testing_pushbutton_Callback(hObject, eventdata, handles) s=rgb2gray(handles.im_testing)

%ubah data menjadi bipolar[1,-1] jml_baris=size(s,1); jml_kolom=size(s,2); for i=1:1:jml_baris for j=1:1:jml_kolom if s(i,j)>=200 %putih s_temp(i,j)=-1; else %hitam s_temp(i,j)=1; end end end

%ubah matrik citra 2 dimensi s_temp jadi vektor 1 dimensi s k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; s_vektor(k)=s_temp(i,j); end end jml_input = k jml_output=handles.jml_target for i=1:jml_output net(i)=0; end size(handles.w_final) for j=1:1:jml_output for i=1:1:jml_input x(i)=s_vektor(i); net(j)=net(j)+x(i)*handles.w_final(i,j); end net(j)=net(j)+handles.b_final(j) end for i=1:jml_output if net(i)>=0 net(i)=1 else

(24)

net(i)=-1 end end jml_pola=size(handles.target,1); cocok=0; axes(handles.axes3); for i=1:jml_pola if handles.target(i,:)==net() imshow(handles.img_original{i}); cocok=1; handles.wav_hasil=strcat('wav',num2str(i),'.wav'); break; end end if cocok==0

h=msgbox('Tidak ada yang cocok','warning'); end

2.4 Hasil Eksekusi (RUN) program

Hasil eksekusi program JST Perceptron dapat dilihat dalam Gambar 2.2.

Cara kerja program :

- Buka file citra atau gambar dengan menekan tombol

open

pada panel training

- Masukkan nilai alpha (misal : 0.7) dan nilai tetha (misal : 0.3). Klik tombol

Start Training, setelah menunggu beberapa saat sistem akan menampilkan

bobot (w) dan bias (b) hasil pelatihan pada list box

- Buka file citra atau gambar dengan menekan tombol open pada panel testing

- Klik tombol Start Testing, selanjutnya akan ditampilkan citra hasil testing yang

cocok dengan citra yang diuji.

(25)

2.5 Latihan

1. Buatlah percobaan dengan menggunakan program aplikasi JST Perceptron

dengan 5 buah citra pola huruf untuk proses pelatihan. Selanjutnya ujilah atau

testing sistem dengan citra huruf yang cacat atau mengandung noise.

2. Buatlah percobaan dengan memakai program aplikasi JST Perceptron dengan 5

buah citra sidik jari untuk proses pelatihan atau training. Kemudian testing

system dengan citra wajah cacat atau mengandung noise

(26)

JST Heteroassociative Memory (HM)

3.1.Rancangan Graphical User Interface (GUI)

3.2 Daftar Komponen

1 ₃

1 ₁

(27)

2.3. Kode Program (source code)

2.3.1 Function

image1_pushbutton

_Callback

handles.image_dir=uigetdir(current_dir,'Select directory'); %Selecting directory %where image saved

No

Komponen

Properti

1 Panel

Title

Training

2 Axes

Tag

axes1

3 Axes

Tag

axes2

4 Push button

String

open

Tag

image1_pushbutton

5 Push button

String

<

Tag

before_pushbutton

6 Push button

String

>

Tag

next_pushbutton

7 Push button

String

<

Tag

before2_pushbutton

8 Push button

String

>

Tag

next2_pushbutton

9 Push button

String

Start Training

Tag

start_trainning_pushbutton

10 Push button

String

open

11 Push button

String

Open testing image

Tag

image_testing_pushbutton

12 Push button

String

Start Testing

Tag

start_testing_pushbutton

No

Komponen

Properti

13 Static text3

String

Weight (w) dan Bias (b)

14 List box

String

kosong

Tag

show_listbox

15 Panel

Title

Testing

16 Static text4

String

Hasil Testing

(28)

%Reading multiple image files at one folder if exist(handles.image_dir)

cd(handles.image_dir); %change directory D = dir('*.jpg');

handles.im_original = cell(1,numel(D));% number element for i = 1:numel(D)

handles.im_original{i} = imread(D(i).name); %save image data into array 'im_original' end axes(handles.axes1); %imshow(imcell{1}); for i=1:numel(D) imshow(handles.im_original{i}); end handles.number_of_image=numel(D); handles.number_of_max=numel(D); else

h=msgbox('file not found', 'Warning','error'); end

2.3.2 Function

before_pushbutton

_Callback

i=handles.number_of_image; if i==1 imshow(handles.im_original{1}); %handles.number_of_img=1; else imshow(handles.im_original{i}); handles.number_of_image = handles.number_of_image-1; end guidata(hObject,handles);

2.3.3 Function

next_pushbutton

_Callback

function next_pushbutton_Callback(hObject, eventdata, handles) i=handles.number_of_image; if i == handles.number_of_max imshow(handles.im_original{i}); %handles.number_of_img=1; else imshow(handles.im_original{i}); handles.number_of_image = handles.number_of_image+1; end guidata(hObject,handles);

2.3.1 Function

image1_target_pushbutton

_Callback

handles.image_dir=uigetdir(current_dir,'Select directory'); %Selecting directory %where image saved

%Reading multiple image files at one folder if exist(handles.image_dir)

cd(handles.image_dir); %change directory D = dir('*.jpg');

handles.im_original = cell(1,numel(D));% number element for i = 1:numel(D)

(29)

end axes(handles.axes2); %imshow(imcell{1}); for i=1:numel(D) imshow(handles.im_original{i}); end handles.number_of_image=numel(D); handles.number_of_max=numel(D); else

h=msgbox('file not found', 'Warning','error'); end

cd(current_dir);%return into current directory guidata(hObject,handles);

2.3.4 Function

before2_pushbutton

_Callback

i=handles.number_of_image_target; if i==1 imshow(handles.im_original_target{1}); %handles.number_of_img=1; else imshow(handles.im_original_target{i}); handles.number_of_image_target = handles.number_of_image_target-1; end guidata(hObject,handles);

2.3.5 Function

next2_pushbutton

_Callback

function next_pushbutton_Callback(hObject, eventdata, handles) i=handles.number_of_image_target; if i == handles.number_of_max_target imshow(handles.im_original_target{i}); %handles.number_of_img=1; else imshow(handles.im_original_target{i}); handles.number_of_image_target = handles.number_of_image_target+1; end guidata(hObject,handles);

2.3.4 Function

_Callback

num_im=size(handles.im_original,2); %number of images for i=1:1:num_im s(i,:,:)=im2bw(handles.im_original{i}); end %s(1,:,:) %size(s) for i=1:1:num_im s_target(i,:,:)=im2bw(handles.im_original_target{i}); end %s_target(1,:,:) %size(s_target) jml_citra=size(s,1); jml_baris=size(s,2); jml_kolom=size(s,3);

(30)

%ubah citra "target" bw menjadi bipolar[1,-1] handles.jml_citra_target=size(s_target,1); handles.jml_baris_target=size(s_target,2); handles.jml_kolom_target=size(s_target,3); for k=1:1:handles.jml_citra_target for i=1:1:handles.jml_baris_target for j=1:1:handles.jml_kolom_target if s_target(k,i,j)> 0 %putih s_target_temp(k,i,j)=-1; else %hitam s_target_temp(k,i,j)=1; end handles.s_target_bipolar(k,i,j)=s_target_temp(k,i,j); end end end %handles.s1_target_bipolar

%ubah citra 'source' format matrik baris kolom(i,j) jadi format baris %citra 1 for m=1:1:jml_citra k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; source(m,k)=s_temp(m,i,j); end end end

%ubah citra 'target' format matrik baris kolom(i,j) jadi format baris %citra target 1 for k=1:1:handles.jml_citra_target m=0; for i=1:1:handles.jml_baris_target for j=1:1:handles.jml_kolom_target m=m+1; target(k,m)=s_target_temp(k,i,j); end end end

(31)

jml_pola=size(source,1); jml_input = size(source,2); jml_output=size(target,2); %handles.jml_baris_target*handles.jml_kolom_target; handles.w=0; for i=1:1:jml_pola handles.w= handles.w+source(i,:)'*target(i,:); end

%%tampilkan bobot dan bias hasil pelatihan dalam command window %for j=1:1:jml_output % for i=1:1:jml_input % disp(strcat('w',num2str(i),num2str(j),' = ',num2str(handles.w(i,j)))); % end %end

%Tampilkan bobot dalam list box %n=0;

%for j=1:1:jml_output %index dari bobot w % for i=1:1:jml_input % n=n+1; % in(n)=i; % jn(n)=j; % wn(n)=handles.w(i,j); % end %end %set(handles.show_listbox,'String',strcat('w',num2str(in'),num2str(jn'),' = ',num2str(wn'))); guidata(hObject,handles);

2.3.5 Function

_Callback

%yang lain

imshow(handles.im_testing); else % if image doesn_t exist

2.3.6 Function

_Callback

function start_testing_pushbutton_Callback(hObject, eventdata, handles) s=im2bw(handles.im_testing);

%ubah data menjadi bipolar[1,-1] jml_baris=size(s,1); jml_kolom=size(s,2); for i=1:1:jml_baris for j=1:1:jml_kolom if s(i,j)>0 %putih s_temp(i,j)=-1; else %hitam s_temp(i,j)=1; end

(32)

end end s_temp

%ubah matrik citra baris-kolom s_temp jadi matrik baris k=0; for i=1:1:jml_baris for j=1:1:jml_kolom k=k+1; s_vektor(k)=s_temp(i,j); end end jml_input = k; jml_output=handles.jml_baris_target*handles.jml_kolom_target; y_temp=s_vektor*handles.w; for j=1:1:jml_output if y_temp(j)>0 y(j)=1; else if y_temp(j)<=0 y(j)=-1; else if y_temp(j)==0 y(j)=0; end end end end

%bandingkan output dengan target axes(handles.axes4); for k=1:handles.jml_citra_target if y==handles.s_target_bipolar(k,:); imshow(handles.im_original{k}); break; end end

2.4 Hasil Eksekusi (RUN) program

(33)

Cara kerja program :

- Buka file citra atau gambar pelatihan (source image(s)) dengan menekan

tombol

open

pada panel training

- Buka file citra atau gambar (target image(t)) dengan menekan tombol

open

pada panel training

- Lakukan proses training dengan menekan tombol Start Training

- Buka file citra atau gambar testing dengan menekan tombol open pada panel

testing

- Klik tombol Start Testing, selanjutnya akan ditampilkan citra hasil testing yang

cocok dengan citra yang diuji.

2.5 Latihan

1. Buatlah percobaan dengan menggunakan program aplikasi JST HM dengan 5

buah citra wajah untuk proses pelatihan. Selanjutnya ujilah atau testing sistem

dengan citra huruf yang cacat atau mengandung noise.

2. Buatlah percobaan dengan memakai program aplikasi JST HM dengan 5 buah

citra sidik jari untuk proses pelatihan atau training. Kemudian testing sistem

dengan citra sidik jari cacat atau mengandung noise

(34)

JST Back Propagation (BP)

4.1.Rancangan Graphical User Interface (GUI)

4.2 Daftar Komponen

1 ₄

1 ₁

(35)

4.3. Kode Program (source code)

No

Komponen

Properti

1 Panel

Title

Training

2 listbox

String

Tag

data_trainning_listbox

3 Push button

String

open data trainning

Tag

data_trainning_pushbutton

4 listbox

String

Tag

data_wb_listbox

5 Push button

String

open weight - bias

Tag

data_wb_pushbutton

6 Static text

String

Jumlah hidden unit

7 Edit text

String

tag

jml_hidden_edit

7 Static text

String

Learning Rate

8 Edit text

String

tag

learning_rate_edit

9 Static text

String

weight(w)-bias(b) after trainning

10 listbox

String

Tag

wb_result_listbox

11 Push button

String

Start Training

Tag

start_training_pushbutton

12 Panel

Title

Testing

13 listbox

String

Tag

data_testing_listbox

14 Push button

String

open data testing

Tag

data_testing_pushbutton

15 listbox

String

Tag

result_listbox

16 Static text

String

Hasil Testing

17 Push button

String

Start Testing

Tag

start_testing_pushbutton

16 Static text

String

Physics, Unud, Bali

(36)

4.3.1 Function

data_trainning_pushbutton

_Callback

[filename,handles.pathname]=uigetfile('*.xls;*.xlsx','Select data trainning'); handles.data_trainning_file = strcat(handles.pathname,filename);

if exist(handles.data_trainning_file) % check if files exists

handles.data_trainning=xlsread(handles.data_trainning_file); % read data trainning in 'excels' file

end

set(handles.data_trainning_listbox,'String',num2str(handles.data_trainning)); guidata(hObject,handles);

4.3.2 Function

data_wb_pushbutton

_Callback

[filename,pathname]=uigetfile('*.xls;*.xlsx','Select data trainning'); handles.wb_file = strcat(pathname,filename);

if exist(handles.wb_file) % check if files exists

handles.wb=xlsread(handles.wb_file); % read data trainning in 'excels' file end

set(handles.data_wb_listbox,'String',num2str(handles.wb)); guidata(hObject,handles);

4.3.3 Function

start_training_pushbutton

_Callback

jml_baris=size(handles.data_trainning,1); jml_kolom=size(handles.data_trainning,2); jml_pola=size(handles.data_trainning,1); jml_input=size(handles.data_trainning,2)-1; jml_output=size(handles.data_trainning,2)-jml_input; jml_hid=str2num(get(handles.jml_hidden_edit,'String')); alpa=str2num(get(handles.learning_rate_edit,'String'));

%reading data source for n=1:1:jml_pola for i=1:1:jml_input s(n,i)= handles.data_trainning(n,i); end end s

%reading data target for n=1:1:jml_pola for i=1:1:jml_output t(n,i)=handles.data_trainning(n,jml_input+i); end end t jml_input jml_hid size(handles.wb) %handles.wb(2,4)

%reading data weight and bias

%reading data weight hidden layer for i=1:1:jml_input for j=1:1:jml_hid v(i,j)=handles.wb(i,j); end end v

(37)

%reading data bias hidden layer for i=1:1:jml_hid

v0(i)=handles.wb(jml_input+1,i); end

v0

%reading data weight output layer for i=1:1:jml_hid for j=1:1:jml_output w(i,j)=handles.wb(jml_input+1+i,j); end end w

%reading data bias output layer for i=1:1:jml_output w0(i)=handles.wb(jml_input+1+jml_hid+1,i); end w0 eps=0.05; tot_err=0; jml_iterasi=0; stop=false; %********Mulai Pelatihan********** while stop==false %%tot_err=0; for n=1:1:jml_pola for j=1:1:jml_hid tot_j=0; for i=1:1:jml_input x(i)=s(n,i); tot_j=tot_j+x(i)*v(i,j); end z_in(j)=v0(j)+tot_j;

%%z[j]=1/(1+exp(-(z_in[j]))); %FUNGSI BINER SIGMOID z(j)=(2/(1+exp(-(z_in(j)))))-1; %FUNGSI BIPOLAR SIGMOID end for k=1:1:jml_output tot_k=0; for j=1:1:jml_hid tot_k=tot_k+z(j)*w(j,k); end y_in(k)=w0(k)+tot_k;

%y[k]=1/(1+exp(-y_in[k])); %FUNGSI BINER SIGMOID y(k)=(2/(1+exp(-y_in(k))))-1; %FUNGSI BIPOLAR SIGMOID end %BACKPROPAGATION %tot_err=0; for k=1:1:jml_output

%fx=1/(1+exp(-y_in[k])); %biner sigmoid %diff=fx*(1-fx);//turunan pertama

fx=(2/(1+exp(-y_in(k))))-1; %Bipolar sigmoid diff=0.5*(1+fx)*(1-fx); %turunan pertama t1(k)=t(n,k); %target

tot_err=tot_err+(t1(k)-y(k))^2; %total error kuadrat del_k(k)=(t1(k)-y(k))*diff; %error

(38)

for j=1:1:jml_hid

delta_w(j,k)=alpa*del_k(k)*z(j); %delta bobot pada unit output end

delta_w0(k)=alpa*del_k(k); %delta bias pd unit output end for j=1:1:jml_hid tot_e_k=0; for k=1:1:jml_output tot_e_k=tot_e_k+del_k(k)*w(j,k); end del_in(j)=tot_e_k;

%fx=1/(1+exp(-z_in(j))); %biner sigmoid %diff=fx*(1-fx); fx=(2/(1+exp(-z_in(j))))-1; diff=0.5*(1+fx)*(1-fx); del_j(j)=del_in(j)*diff; for i=1:1:jml_input x(i)=s(n,i);

delta_v(i,j)=alpa*del_j(j)*x(i); %delta bobot pd unit hidden end

delta_v0(j)=alpa*del_j(j); %delta bias pd unit hidden end

%UBAH BOBOT DAN BIAS

%Ubah bobot unit output for j=1:1:jml_hid

for k=1:1:jml_output

w(j,k)=w(j,k)+delta_w(j,k); end

end

%ubah bias unit output for k=1:1:jml_output

w0(k)=w0(k)+delta_w0(k); end

%ubah bobot unit hidden for i=1:1:jml_input for j=1:1:jml_hid

v(i,j)=v(i,j)+delta_v(i,j); end

end

%ubah bias unit hidden for j=1:1:jml_hid v0(j)=v0(j)+delta_v0(j); end end %for n if tot_err>eps %continue tot_err=0; jml_iterasi=jml_iterasi+1 stop=false; else %stop stop=true; end

end %while stop

%saving trainning result into excels file

v(jml_input+1,:)=v0; %bias unit hiden

(39)

for i=1:1:jml_hid

v(jml_input+1+i,1)=w(i); %bobot unit output end

for i=1:1:jml_output

v(jml_input+1+jml_hid+i,1)=w0(i); %bias unit output end

%simpan bobot w dan bias b dalam excel file if exist(strcat(handles.pathname,'bobot_hasil_backprop.xls')); delete (strcat(handles.pathname,'bobot_hasil_backprop.xls')); xlswrite(strcat(handles.pathname,'bobot_hasil_backprop.xls'),v); else xlswrite(strcat(handles.pathname,'bobot_hasil_backprop.xls'),v); end set(handles.wb_result_listbox,'String',num2str(v));

%%tampilkan bobot dan bias hasil pelatihan dalam comman window %for j=1:1:jml_output % for i=1:1:jml_input % disp(strcat('w',num2str(i),num2str(j),' = ',num2str(handles.w(i,j)))); % end %end

%Tampilkan bobot dalam list box %n=0;

%for j=1:1:jml_output %index dari bobot w % for i=1:1:jml_input % n=n+1; % in(n)=i; % jn(n)=j; % wn(n)=handles.w(i,j); % end %end %set(handles.wb_result_listbox,'String',strcat('w',num2str(in'),num2str(jn'),' = ',num2str(wn'))); guidata(hObject,handles);

4.3.4 Function

data_testing_pushbutton

_Callback

[filename,pathname]=uigetfile('*.xls;*.xlsx','Select data trainning'); handles.data_testing_file = strcat(pathname,filename);

if exist(handles.data_testing_file) % check if files exists

handles.data_testing=xlsread(handles.data_testing_file); % read data trainning in 'excels' file

end

set(handles.data_testing_listbox,'String',num2str(handles.data_testing')); guidata(hObject,handles);

4.3.5 Function

_Callback

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jml_input=size(handles.data_trainning,2)-1; jml_output=size(handles.data_trainning,2)-jml_input; jml_hid=str2num(get(handles.jml_hidden_edit,'String')); alpa=str2num(get(handles.learning_rate_edit,'String'));

%reading data source for i=1:1:jml_input

x(i)= handles.data_testing(1,i); end

%read weight and bias of trainning

wb_testing=xlsread(strcat(handles.pathname,'bobot_hasil_backprop.xls'));

%reading data weight of hidden layer , v for i=1:1:jml_input for j=1:1:jml_hid v(i,j)=wb_testing(i,j); end end v

%reading data bias hidden layer, v0 for i=1:1:jml_hid

v0(i)=wb_testing(jml_input+1,i); end

v0

%reading data weight output layer, w for i=1:1:jml_hid for j=1:1:jml_output w(i,j)=wb_testing(jml_input+1+i,j); end end w

%reading data bias output layer , w0 for i=1:1:jml_output w0(i)=wb_testing(jml_input+1+jml_hid+1,i); end w0 %proses Testing for j=1:1:jml_hid tot=0; for i=1:1:jml_input tot=tot+x(i)*v(i,j); end z_in(j)=v0(j)+tot;

%z(j)=1/(1+exp(-z_in(j))); %biner sigmoid z(j)=(2/(1+exp(-z_in(j))))-1; %bipolar sigmoid end for k=1:1:jml_output tot=0; for j=1:1:jml_hid tot=tot+z(j)*w(j,k); end y_in(k)=w0(k)+tot; %y[k]=1/(1+exp(-y_in[k])); y(k)=(2/(1+exp(-y_in(k))))-1; end set(handles.result_listbox,'String',num2str(y')); %set(handles.wb_result_listbox,'String',list_box_new) ; y

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