Saran

BAB V PENUTUP

5.2 Saran

Penelitian ini memiliki banyak kekurangan dan masih bisa dikembangkan lagi pada penelitian berikutnya, maka ada beberapa saran yang dapat disampaikan untuk mengembangkan penelitian ini :

a. Penelitian selanjutnya dapat menggunakan dan membandingkan dengan metode model ruang warna lainnya seperti Hue Saturation Value.

b. Objek yang terdeteksi dapat dikembangkan tidak hanya kematangan warna, dapat juga mendeteksi cabai rawit yang busuk.

Ruang Warna Hue Saturation Intensity (HSI) untuk Mendeteksi Kematangan Buah Mangga Harum Manis. Jurnal Komputer dan Aplikasi, Volume 8, pp. 1-10.

Harianto, K., Pratiwi, H. & Suhariyadi, Y., 2019. Sistem Monitoring Lulusan Perguruan tinggi dalam memasuki dunia kerja menggunakan tracer study.

Media Sahabat Cendikia.

Kadir, A. & Susanto, A., 2013. Teori dan Aplikasi Pengolahan Citra. Yogyakarta:

Andi Yogyakarta.

M., 2015. Metodologi Kualitatif. Sidoarjo: Zifatama.

Muharni, S., 2020. Analisa dan Perancangan Sistem Informasi. Yogyakarta: CV.

Bintang Pustaka Madani.

Nugroho, A., 2017. Pemrograman Berorientasi Objek Menggunakan C#.

Yogyakarta: Andi.

Payadnya, I. P. A. A. & Jayantika, I. G. A. N. T., 2018. Panduan Penelitian Eksperimen Beserta Analisis Statistik Dengan SPSS. Yogyakarta: Cv Budi Utama.

Prajnata, F., 2011. Mengatasi Permasalahan Bertanam Cabai. Jakarta: s.n.

Pratama, R., Assagaf, A. F. & Tempola, F., 2019. Deteksi Kematangan Buah Tomat Berdasarkan FIitur Warna. Jurnal Informatika dan Komputer, Volume 2, pp. 81-86.

Sitorus, L., 2015. Algoritma Dan Pemrograman. Yogyakarta: Cv Andi Ofset.

Sutoyo. et al., 2020. Penerapan Metode Transformasi Ruang Warna HSI untuk Mendeteksi Tingkat Kematangan Buah Pisang Berdasarkan Fitur Warna Citra Kulit. Jurnal Penelitian dan Aplikasi Sistem & Teknik Industri, Volume XIV, p. 245.

Syukur, M., Yunianti, R. & Dermawan, R., 2013. Sukses Panen Cabai Tiap Hari.

Jakarta: s.n

Tohari, H., 2014. Analisis serta Perancangan Sistem Informasi melalui Pendekatan UML. Yogyakarta: Andi.

Wandi, D., F. & Hayati, N., 2021. Deteksi Kelayuan Bunga Mawar Dengan Metode Transformasi Ruang Warna HSI Dan HSV. Satuan Tulisan Riset dan Inovasi Teknologi, Volume 2.

Yanto, B. et al., 2021. Klarifikasi Kematangan Buah Nanas Dengan Ruang Warna Hue Saturation Intensity. Jurnal Inovtek Pplbeng - Seri Informatika,, Volume 6.

Zed, M., 2014. Metode Penelitian Kepustakaan. Jakarta: Yayasan Pustaka Obor Indonesia.

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Lampiran 5 Source code

function varargout = meilyGUI(varargin) gui_Singleton = 1;

gui_State = struct('gui_Name', mfilename, ...

if nargin && ischar(varargin{1})

gui_State.gui_Callback = str2func(varargin{1});

end if nargout

[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});

else

gui_mainfcn(gui_State, varargin{:});

end

function meilyGUI_OpeningFcn(hObject, eventdata, handles, varargin)

global data_temp data_temp.MyData = [];

handles.output = hObject;

guidata(hObject, handles);

function varargout = meilyGUI_OutputFcn(hObject, eventdata, handles)

varargout{1} = handles.output;

function pushbutton1_Callback(hObject, eventdata, handles)

[filename,pathname] = uigetfile( ...

{'*.bmp;*.jpg;*.tif','Files of type (*.bmp,*.jpg,*.tif)';

'*.bmp','File Bitmap (*.bmp)';...

Gambar = imread(fullfile(pathname,filename));

axes(handles.axes26)

red = mean(mean(handles.Img(:,:,1)));

green = mean(mean(handles.Img(:,:,2)));

blue = mean(mean(handles.Img(:,:,3)));

Gambar = handles.Img;

showred = Gambar(:,:,1);

axes(handles.axes22);

imshow(showred);

guidata(hObject,handles);

Gambar = handles.Img;

showgreen = Gambar(:,:,2);

axes(handles.axes23);

imshow(showgreen);

guidata(hObject,handles);

Gambar = handles.Img;

showblue = Gambar(:,:,3);

axes(handles.axes24);

function blue_CreateFcn(hObject, eventdata, handles)

function text17_CreateFcn(hObject, eventdata, handles)

function varargout = Main(varargin) gui_Singleton = 1;

gui_State = struct('gui_Name', mfilename, ...

if nargin && ischar(varargin{1})

gui_State.gui_Callback = str2func(varargin{1});

end if nargout

[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});

else

gui_mainfcn(gui_State, varargin{:});

end

function Main_OpeningFcn(hObject, eventdata, handles, varargin)

handles.output = hObject;

guidata(hObject, handles);

function varargout = Main_OutputFcn(hObject, eventdata, handles)

varargout{1} = handles.output;

function pushbutton1_insert_Callback(hObject, eventdata, handles)

[filename,pathname] = uigetfile('*.jpg');

Img = imread(fullfile(pathname,filename));

handles.I = Img; eventdata, handles)

% pisah rgb Img = handles.I;

%cari nilai HSI

RGB = im2double(Img);

teta = acosd(atas./(bawah));

if Blue >= Green

%isi dalam tabel MeanR = mean2(Red);

MeanG = mean2(Green);

MeanB = mean2(Blue);

MeanH = mean2(H);

MeanS = mean2(S);

MeanI = mean2(I);

VarRed = var(Red(:));

VarGreen = var(Green(:));

VarBlue = var(Blue(:));

VarH = var(H(:));

VarS = var(S(:));

VarI = var(I(:));

RangeR = ((max(max(Red)))-(min(min(Red))));

RangeG = ((max(max(Green)))-(min(min(Green))));

RangeB = ((max(max(Blue)))-(min(min(Blue))));

RangeH = ((max(max(H)))-(min(min(H))));

RangeS = ((max(max(S)))-(min(min(S))));

RangeI = ((max(max(I)))-(min(min(I))));

data = get(handles.uitable2,'Data');

data{1,1} = num2str(MeanR);

data{2,1} = num2str(MeanG);

data{3,1} = num2str(MeanB);

data{4,1} = num2str(MeanH);

data{5,1} = num2str(MeanS);

data{6,1} = num2str(MeanI);

data{1,2} = num2str(VarRed);

data{2,2} = num2str(VarGreen);

data{3,2} = num2str(VarBlue);

data{4,2} = num2str(VarH);

data{5,2} = num2str(VarS);

data{6,2} = num2str(VarI);

data{1,3} = num2str(RangeR);

data{2,3} = num2str(RangeG);

data{3,3} = num2str(RangeB);

data{4,3} = num2str(RangeH);

data{5,3} = num2str(RangeS);

data{6,3} = num2str(RangeI);

set(handles.uitable2,'Data',data,'ForegroundColor', [0 0 0])

training1 = xlsread('Data Training');

group = training1(:,25);

training = [training1(:,1) training1(:,2) training1(:,3) training1(:,4) training1(:,5) training1(:,6)

training1(:,7) training1(:,8) training1(:,9) training1(:,10) training1(:,11) training1(:,12) training1(:,13) training1(:,14) training1(:,15) training1(:,16) training1(:,17) training1(:,18)];

Z=[MeanR MeanG MeanB MeanH MeanS MeanI VarRed VarGreen VarBlue VarH VarS VarI RangeR RangeG RangeB RangeH RangeS RangeI];

hasil1=knnclassify(Z,training,group);

image_folder = 'E:\Program Deteksi Kematangan Cabai\Datacabai\matang';

filenames = dir(fullfile(image_folder, '*.jpg'));

total_images = numel(filenames);

Z1=[];

for n = 1:total_images

full_name= fullfile(image_folder, filenames(n).name);

Img = imread(full_name);

%cari nilai HSI

RGB = im2double(Img);

teta = acosd(atas./(bawah));

if Blue >= Green

MeanR = mean2(Red);

MeanG = mean2(Green);

MeanB = mean2(Blue);

MeanH = mean2(H);

MeanS = mean2(S);

MeanI = mean2(I);

VarRed = var(Red(:));

VarGreen = var(Green(:));

VarBlue = var(Blue(:));

VarH = var(H(:));

VarS = var(S(:));

VarI = var(I(:));

RangeR = ((max(max(Red)))-(min(min(Red))));

RangeG = ((max(max(Green)))-(min(min(Green))));

RangeB = ((max(max(Blue)))-(min(min(Blue))));

RangeH = ((max(max(H)))-(min(min(H))));

RangeS = ((max(max(S)))-(min(min(S))));

RangeI = ((max(max(I)))-(min(min(I))));

sdR = std2(Red);

sdG = std2(Green);

sdB = std2(Blue);

sdH = std2(H);

sdS = std2(S);

sdI = std2(I);

Z=[MeanR MeanG MeanB MeanH MeanS MeanI VarRed VarGreen VarBlue VarH VarS VarI RangeR RangeG RangeB RangeH RangeS RangeI sdR sdG sdB sdH sdS sdI 1];

Z1=[Z1;Z];

end

image_folder = 'E:\Program Deteksi Kematangan Cabai\Datacabai\setengah matang';

filenames = dir(fullfile(image_folder, '*.jpg'));

total_images = numel(filenames);

for n = 1:total_images

full_name= fullfile(image_folder, filenames(n).name);

Img = imread(full_name);

%cari nilai HSI

RGB = im2double(Img);

teta = acosd(atas./(bawah));

if Blue >= Green

end end

%I

I=(Red+Green+Blue)/3;

MeanR = mean2(Red);

MeanG = mean2(Green);

MeanB = mean2(Blue);

MeanH = mean2(H);

MeanS = mean2(S);

MeanI = mean2(I);

VarRed = var(Red(:));

VarGreen = var(Green(:));

VarBlue = var(Blue(:));

VarH = var(H(:));

VarS = var(S(:));

VarI = var(I(:));

RangeR = ((max(max(Red)))-(min(min(Red))));

RangeG = ((max(max(Green)))-(min(min(Green))));

RangeB = ((max(max(Blue)))-(min(min(Blue))));

RangeH = ((max(max(H)))-(min(min(H))));

RangeS = ((max(max(S)))-(min(min(S))));

RangeI = ((max(max(I)))-(min(min(I))));

sdR = std2(Red);

sdG = std2(Green);

sdB = std2(Blue);

sdH = std2(H);

sdS = std2(S);

sdI = std2(I);

Z=[MeanR MeanG MeanB MeanH MeanS MeanI VarRed VarGreen VarBlue VarH VarS VarI RangeR RangeG RangeB RangeH RangeS RangeI sdR sdG sdB sdH sdS sdI 2];

Z1=[Z1;Z];

end

image_folder = 'E:\Program Deteksi Kematangan Cabai\Datacabai\mentah';

filenames = dir(fullfile(image_folder, '*.jpg'));

total_images = numel(filenames);

for n = 1:total_images

full_name= fullfile(image_folder, filenames(n).name);

Img = imread(full_name);

%cari nilai HSI

RGB = im2double(Img);

teta = acosd(atas./(bawah));

if Blue >= Green

MeanR = mean2(Red);

MeanG = mean2(Green);

MeanB = mean2(Blue);

MeanH = mean2(H);

MeanS = mean2(S);

MeanI = mean2(I);

VarRed = var(Red(:));

VarGreen = var(Green(:));

VarBlue = var(Blue(:));

VarH = var(H(:));

VarS = var(S(:));

VarI = var(I(:));

RangeR = ((max(max(Red)))-(min(min(Red))));

RangeG = ((max(max(Green)))-(min(min(Green))));

RangeB = ((max(max(Blue)))-(min(min(Blue))));

RangeH = ((max(max(H)))-(min(min(H))));

RangeS = ((max(max(S)))-(min(min(S))));

RangeI = ((max(max(I)))-(min(min(I))));

sdR = std2(Red);

sdG = std2(Green);

sdB = std2(Blue);

sdH = std2(H);

sdS = std2(S);

sdI = std2(I);

Z=[MeanR MeanG MeanB MeanH MeanS MeanI VarRed VarGreen VarBlue VarH VarS VarI RangeR RangeG RangeB RangeH RangeS RangeI sdR sdG sdB sdH sdS sdI 3]; eventdata, handles)

if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) set(hObject,'BackgroundColor','white');

end

function edit2_hasil_Callback(hObject, eventdata, handles)

function edit2_hasil_CreateFcn(hObject, eventdata, handles)

if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))

set(hObject,'BackgroundColor','white');

end

function uitable2_CellEditCallback(hObject, eventdata, handles)

function text1_CreateFcn(hObject, eventdata, handles)

function text2_CreateFcn(hObject, eventdata, handles)

function uitable2_CellSelectionCallback(hObject, eventdata, handles)

function axes1_CreateFcn(hObject, eventdata, handles)

function uipanel1_CreateFcn(hObject, eventdata, handles)