Download - ITS Undergraduate 12352 Presentation
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 1/30
IDENTIFIKASI VARIETAS UNGGUL KEDELAI
BERDASARKAN WARNA DENGANFUZZY CLUSTER MEANS
Oleh:
Dwi Lastomo
1105 100 054
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 2/30
Menu Tugas Akhir
BAB IPENDAHULUAN
BAB II
BAB IV
ANALISIS DATA &
PEMBAHASAN
BAB III
METODOLOGI
PERCOBAAN
BAB V
KESIMPULAN & SARAN
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 3/30
BAB I Pendahuluan
1.1. LATAR BELAKANG
PENDAHULUAN
1.5. MANFAAT1.4. TUJUAN
. ..
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 4/30
Latar Belakang
1. Kedelai Komodoti yang Penting
2. Kesulitan memilah bibit yang baik
1. SORTIRManual2. SORTIR Alat Mekatronik
3. Klaster K-Means
4. Jaringan Syaraf Tiruan
5. FUZZY CLUSTER MEANS
BIBIT yang baik
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 5/30
Rumusan Masalah
Memperoleh klaster biji kedelai
melalui Metode FCM
Batasan Masalah
Metode FCM
ToolBox Matlab
Data
Hardare
Tujuan
Memperoleh klaster biji kedelai melaui
metode FCM, hasilnya dibandingkan
dengan metode JST Manfaat
Mendapatakan klaster optimum
untuk memilah varietas unggul
kedelai
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 6/30
BAB II TINJAUAN PUATAKA
KEDELAI
KLASTER
FUZZY CLUSTER MEANS (FCM)
CAHAYA, WARNA, & RGB
FUZZY
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 7/30
• KEDELAI
•
Klasifikasi ilmiah – Kerajaan : Plantae
– Filum : Magnoliophyta
– Kelas : Magnoliopsida
– r o : a a es
– Famili : Fabaceae
– Upafamili : Faboideae
– Genus : Glycine (L.) Merr.
– Spesies:
• Glycine max • Glycine soja
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 8/30
BAHAN
MAKANAN
PROTEIN
(% BERAT)
Susu skim kering 36,00
Kedelai 35,00
Kacang hijau 22,00
Daging 19,00Ikan segar 17,00
Telur ayam 13,00
Jagung 9,20
KandunaganKedelai KADAR (%)
Protein 35-45
Lemak 18-32
Karbohidrat 12-30Air 7
Beras 6,80
Tepung singkong 1,10 Nama bahan Makanan Harga/kg
kacang kedelai 8000
kacang hijau 12000
telur ayam 11000
daging sapi 56000
daging ayam 20000
http://www.jatimprov.go.id, 11 -01-2010
http://www.warintek.ristek.go.id
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 9/30
Tabel 2.1
Deskripsi Beberapa Varietas Unggul
KedelaVarietas Warna Kulit Biji Warna Hilum Bobot 100 Biji
Anjasmoro Kuning Kuning Kecoklatan 14,8 – 15,3 g
, – ,
Argopuro Kuning Coklat muda 15,75 g
Panderman Kuning Muda Coklat tua 18 – 19 g
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 10/30
Tabel 2.2.Karakteristik Varietas Unggul
Nama
Varietas
Tahun
Dilepas
Umur
Masak
(hari)
Kadar
Protein (%)
Kadar
Minyak
(%)
Potensi
Hasil
(ton/ha)
Agromulyo 1998 81 39,4 20,8 2,00
Anjasmoro 2001 88 42,1 18,6 2,25
Panderman 2003 85 35,9 17,7 2,37
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 11/30
• 2.2. Klaster
Metode antara lain:
1. Hard C-Means Clustering
(biasa disebut K-means)2. Fuzzy C-means Clustering
3. Mountain Clustering
4. Subtractive Clustering
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 12/30
FUZZY• Fuzzy adalah salah satu dari kecerdasan
buatan untuk mendefinisikan dari bahasalingustik menjadi numerik. Logika ini banyak
-
bersifat abstrak menjadi terukur, tentunya
dengan parameter-parameter yang telah
ditentukan sebelumnya
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 13/30
FUZZY CLUSTER MEANS
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 14/30
CAHAYA, WARNA, DAN RGB
Teori Cahaya:
1. Abu Ali Hasan Ibn Al-
Haitham (965–sekitar 1040)
SUMBER CAHAYA
Proses penguraian
Cahaya Putih oleh Prisma
.
Partikel)3. Christiaan Huygens abad
ke-17 (teori gelombang)
4. Faraday 1845 (Teori EM )
5. Max Planck abad ke-19
(teori Kuantum)6. Albert Einstein abad 20
(dualisme partikel
gelombang)
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 15/30
Color Wavelength Sample
Red 700nm
Cahaya yang dapat
ditangkap indera manusia
mempunyai panjang
elomban 380 sam ai
Orange 650nm
Yellow 600nm
Green 550nm
Blue 500nm
Indigo 450nm
Violet 400nm
780 nanometer.
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 16/30
=
i
i
i
i
i
i
B
G
R
Z
Y
X
099.0010.0000.0
011.0813.0177.0
200.0310.0490.0
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 17/30
BAB III
METODOLOGI PENELITIAN
Studi Literatur dan Pengenalan Software Matlab 7.0
Pengumpulan
Data
Hasil
Pengolahan Data
dengan FCM
ToolBox Matlab
7.0
Pengolahan
Data dengan
JST Matlab 6.5
Komparasi
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 18/30
BAB IV
ANALISIS DATA DAN PEMBAHASANVarietas R G B
Anjasmoro 159.69 122.664 19.431
Anjasmoro 176.082 129.462 20.602
Anjasmoro 171.809 133.04 19.39
Anjasmoro 180.187 137.04 23.068
Anjasmoro 181.064 145.409 24.162
Argomulyo 157.045 132.465 15.685
Argomulyo 166.715 131.527 17.687
Sampel Data dari Variasi
Pengambilan Data dengan LampuHalogen pada Kotak Hitam
Argomulyo 169.652 138.028 19.356
Argomulyo 159.027 134.606 17.448
Argomulyo 177.316 145.144 23.911
Argopuro 136.944 113.085 14.995
Argopuro 142.528 118.807 17.528
Argopuro 140.918 116.345 13.914
Argopuro 147.347 116.265 15.003
Argopuro 134.371 124.548 14.514
Panderman 168.064 129.004 21.336
Panderman 172.049 116.349 15.948
Panderman 163.882 132.064 21.554
Panderman 169.538 133.574 21.428
Panderman 152.556 129.168 16.196
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 19/30
Plot data Vektor RGB
0.7
0.8
0.9
1Plot Data Normalisasi
0 10 20 30 40 50 60 70 800
0.1
0.2
0.3
0.4
0.5
0.6
Anggota Data
V e k t o r R
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 20/30
Plot Pusat KLASTER
0.68
0.7
0.72
0.74plot Center of Cluster
0 10 20 30 40 50 60 70 80
0.58
0.6
0.62
0.64
0.66
Anggota Data
V e k t o r R
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 21/30
PLOT DATA DAN PUSAT KLASTER
0.6
0.7
0.8
0.9
1Plot Data Normalisasi dan Center of Cluster
0 10 20 30 40 50 60 70 800
0.1
0.2
0.3
0.4
0.5
DAta anggota
V e k t o r R
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 22/30
PLOT DERAJAT KEANGGOTAAN TIAP
DATA
0.8
0.9
1
derajat keanggotaan
cluster1
cluster2
cluster3
cluster4
0 10 20 30 40 50 60 70 800
0.1
0.2
0.3
0.4
0.5
0.6
.
data ke
d e r a j a t k e a n g g o t a a
n
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 23/30
Tabel 4.2. Pusat Klaster
Varietas X Y
Argopuro 50.906 0.49948
Panderman 71.427 0.59269
Argomulyo 30.098 0.51062
Anjasmoro 9.5745 0.47433
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 24/30
Tabel 4.3. Jarak dan Standar Deviasi
VarietasVarietasVarietasVarietas
Pusat Klaster Pusat Klaster Pusat Klaster Pusat Klaster
JarakJarakJarakJarakRataRataRataRata----ratarataratarata
Standar Standar Standar Standar DeviasiDeviasiDeviasiDeviasiXXXX Y
Anjasmoro 9.5747 0.81388 4.50583937 2.65748
Argomulyo 30.098 0.51062 4.52111802 2.663602
Argopuro 50.906 0.49948 4.50884334 2.689555
Panderman 71.427 0.59269 4.50854114 2.656206
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 25/30
Error Fuzzy dan Keanggotaan ObjekHalogen Coklat Pijar Coklat Halogen Coklat
∑(St.Dev+
jarak
No sample
Anggota
∑(St.Dev+
jarak Rata-
No sample
Anggota ∑ (St.Dev +
No
sample
Anggota
Var etas Rata0rata K aster error rata K aster error ara Rata-rata K aster error
Anjasmoro 7.161637 nomor 3-16 30% 7.16711437 nomor 3-16 30% 7.159671 nomor 3-16 30%
Argomulyo 7.184225 nomor 3-17 25% 7.18472002 nomor 3-17 25% 7.18386 nomor 3-17 25%
Argopuro 7.190032 nomor 4-18 25% 7.19839834 nomor 4-18 25% 7.19322 nomor 4-18 25%
Panderman 7.163145 nomor 5-18 30% 7.16474714 nomor 5-18 30% 7.157925 nomor 5-18 30%
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 26/30
Tabel Hasil Pelatihan untuk Pengenalan
Anjasmoro
No. Data Pelatihan Jaringan Epoch MSE
1 60 3-100-1 1027 3.33E-02
- - . -
3 60 3-300-1 267 9.95E-06
4 60 3-400-1 625 9.81E-06
5 60 3-500-1 617 9.31E-06
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 27/30
Hasil Pengujian Anjasmoro dari
Jaringan pada Tabel sebelumnya
No.Jumlah
Data
Validasi
Jaringan RMSE
1 20 3-100-1 0.15
2 20 3-200-1 0.15
3 20 3-300-1 0.2802
4 20 3-400-1 0.1
5 20 3-500-1 0.1231
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 28/30
4.3. Pembahasan
Nilai Pusat Klaster selalu berada
Perbedaan nilai RGB untuk tiap
variasi cara pengambilan data
i tenga -tenga e as
Error 25% dan 30%
Derajat keanggotaan vekot RBG
mengikuti logika Fuzzy
Berdasarkan nilai error Fuzzy lebih
konsisten daripada JST, JST lebih akurat
5/14/2018 ITS Undergraduate 12352 Presentation - slidepdf.com
http://slidepdf.com/reader/full/its-undergraduate-12352-presentation 29/30
BAB V KESIMPULAN & SARAN
FCM dapat
mengelompokkan
FCM dapat mengelompokkan tanpa
memasukkan data ke dalam dua klaster (sesuai
derajat keanngoaan dalam fuzzy)
Nilai error dala
Dilakukan penelitian dengan perpaduan
metode ini, yaitu neoro fuzzy SARAN
KESIMPULAN
varietasnya
en as
25%-30%
JST lebih akurat,FCM lebih konsisten