Implementasi Algoritma Neural Network Backpropagation dengan Nguyen

Widrow untuk Penyakit Jantung Koroner pada RSAU dr Esnawan

Antariksa Halim Perdana Kusuma

SKRIPSI

Disusun Oleh:

Muslim Satrio

1510511038

UNIVERSITAS PEMBANGUNAN NASIONAL “VETERAN” JAKARTA

FAKULTAS ILMU KOMPUTER

PROGRAM STUDI INFORMATIKA

2019

i

Implementasi Algoritma Neural Network Backpropagation dengan Nguyen

Widrow untuk Penyakit Jantung Koroner pada RSAU dr Esnawan

Antariksa Halim Perdana Kusuma

SKRIPSI

Diajukan Sebagai Syarat Untuk Meraih Gelar Sarjana Komputer

Disusun Oleh:

Muslim Satrio

1510511038

Halaman Judul

UNIVERSITAS PEMBANGUNAN NASIONAL “VETERAN” JAKARTA

FAKULTAS ILMU KOMPUTER

PROGRAM STUDI INFORMATIKA

2019

ii

PERNYATAAN ORISINALITAS

iii

PERNYATAAN PERSETUJUAN PUBLIKASI SKRIPSI UNTUK

KEPENTINGAN AKADEMIS

iv

PENGESAHAN

v

Implementasi Algoritma Neural Network Backpropagation

dengan Nguyen Widrow untuk Penyakit Jantung Koroner

pada RSAU dr Esnawan Antariksa Halim Perdana Kusuma

Muslim Satrio

ABSTRAK

Penyakit Jantung Koroner peringkat pertama dari 10 penyebab kematian

di dunia. Menurut data WHO 15,2 juta jiwa meninggal dunia pada tahun 2016

akibat jantung koroner. Penyakit Jantung koroner di Indonesia menjadi penyebab

kematian tertinggi di semua umur. Penyebab timbulnya PJK tidak lepas dari pola

hidup yang kurang sehat. Faktor pemicu jantung koroner yaitu kebiasaan konsumsi

akohol,merokok, obesitas, tekanan darah tinggi,diabetes,riwayat keturunan PJK,

kurang aktivitas,jenis kelamin dan stress. Penyakit jantung koroner tidak mudah

terlihat seperti penyakit kulit, tumor, patah tulang atau penyakit infeksi.Beberapa

pasien hanya menampakkan gejala yang samar samar, bahkan ada yang tanpa

keluhan sama sekali.Tujuan Penulis ingin membuat aplikasi untuk membantu

mengidentifikasi Penyakit Jantung koroner dengan Algoritma Neural Network

Backpropagation dan Nguyen widrow. Hasil dari 72 percobaan dalam proses

training dengan kombinasi learning rate dan jumlah hidden layer di dapatkan

arsitektur yang tepat 10-6-3-1 dengan learning rate 0,1 dengan nilai akurasi

99,4047% dan nilai sebesar MSE 0,01271 Saat dilakukan Testing di dapatkan hasil

akurasi 97,46%,nilai mse sebesar 0.012658, sensitivity 96,66%,Specificity 95,23%,

Precision 98,24 %, Error rate 3,34 %.

Kata Kunci : Neural Network, Backpropagation,Nguyen Widrow,Jantung Koroner

vi

Implementation of Backpropagation Neural Network Algorithm

with Nguyen Widrow for Coronary Heart Disease at RSAU

dr. Esnawan Antariksa Halim Perdana Kusuma

Muslim Satrio

ABSTRACT

Coronary Heart Disease ranks first among the 10 causes of death in the world.

According to WHO data 15.2 million people died in 2016 due to coronary heart

disease. Coronary heart disease in Indonesia is the highest cause of death in all ages.

The cause of CHD is inseparable from an unhealthy lifestyle. The trigger factors

for coronary heart disease are alcohol consumption, smoking, obesity, high blood

pressure, diabetes, a history of CHD descent, lack of activity, gender and stress.

Coronary heart disease is not easily seen as a skin disease, tumor, fracture or

infectious disease. Some patients only show vague symptoms, some even have no

complaints at all. Purpose The author wants to make an application to help identify

coronary heart disease with the Neural Network Algorithm Backpropagation and

Nguyen widrow. The results of 72 experiments in the training process with a

combination of learning rate and the number of hidden layers in getting the right

architecture 10-6-3-1 with a learning rate of 0.1 with an accuracy value of

99.4047% and a value of MSE 0.01271 when testing get an accuracy of 97.46%, a

value of 0.012658, sensitivity 96.66%, Specificity 95.23%, Precision 98.24%, Error

rate 3.34%.

Keyword : Neural Network, Backpropagation,Nguyen Widrow,Coronary Heart Disease

vii

KATA PENGANTAR

Segala puji syukur penulis panjatkan kehadirat Allah SWT, Pemelihara seluruh

alam raya, yang atas limpahan rahmat, taufik dan hidayah-Nya, penulis mampu

menyelesaikan Skripsi yang berjudul “Implementasi Algoritma Neural Network

Backpropagation dengan Nguyen Widrow untuk Penyakit Jantung Koroner pada RSAU Dr

Esnawan Antariksa Halim Perdana Kusuma” dapat diselesaikan.

Pada kesempatan ini penulis menyampaikan penghargaan dan ucapan terima kasih

kepada:

a. Orang tua penulis yaitu bapak Andi Taufik dan ibu kadinem tercinta yang telah

memberikan semangat dan membantu penulis dari segi materi dan moril sehingga

penulis dapat menyelesaikan Tugas Akhir ini dengan sebaik – baiknya.

b. Ibu Dr. Ermatita, M.Kom. selaku Dekan Fakultas Ilmu Komputer Universitas

Pembangunan Nasional “Veteran” Jakarta.

c. Ibu Anita Muliawati , S.Kom, M.Ti selaku Ketua Program Studi jurusan

Informatika Fakultas Ilmu Komputer Universitas Pembangunan Nasional

“Veteran” Jakarta.

d. Ibu Yuni Widiastiwi S.Kom M.Si. selaku Dosen Pembimbing I dan Bapak Indra

Solihin, S.Kom M.Kom.CCNA selaku Dosen Pembimbing II yang telah

membantu penulis dalam menyelesaikan Skripsi ini dengan menyumbangkan ilmu

pengetahuan serta arahan.

e. Serta teman-teman jurusan teknik Informatika yang telah berbagi informasi yang

berkaitan dengan Tugas Akhir.

Penulis tahu bahwa dalam penulisan skripsi ini masih banyak kekurangan nya,

penulis mengharapkan saran ataupun kritik yang bersifat membangun agar dikemudian hari

penulis akan menjadi lebih baik lagi. Semoga skripsi ini bermanfaat bagi para pembaca.

Jakarta 3 Juni 2019

Penulis

viii

DAFTAR ISI

HALAMAN JUDUL ............................................................................................... i

PERNYATAAN ORISINALITAS ......................................................................... ii

PERNYATAAN PERSETUJUAN PUBLIKASI .................................................. iii

PENGESAHAN ..................................................................................................... iv

ABSTRAK .............................................................................................................. v

ABSTRACT ........................................................................................................... vi

KATA PENGANTAR .......................................................................................... vii

DAFTAR ISI ........................................................................................................ viii

DAFTAR GAMBAR ............................................................................................. xi

DAFTAR TABEL ................................................................................................. xii

DAFTAR LAMPIRAN ......................................................................................... xii

BAB I ...................................................................................................................... 1

I.1 Latar Belakang ............................................................................................... 1

I.2 Rumusan Masalah .......................................................................................... 2

I.3 Tujuan Penelitian ........................................................................................... 2

I.4 Manfaat Penelitian ......................................................................................... 3

I.5 Ruang Lingkup .............................................................................................. 3

I.6 Luaran Yang Diharapkan ............................................................................... 4

I.7 Sistematika Penulisan .................................................................................... 4

BAB II ..................................................................................................................... 6

II.1Jantung Koroner ............................................................................................ 6

II.1.1 Definisi .................................................................................................. 6

II.1.2 Penyebab Jantung Koroner ................................................................... 6

II.2 Data Mining ............................................................................................... 8

II.2.1 Definisi ................................................................................................... 8

II.2.2 Tahapan Data Mining ............................................................................ 9

II.3 Kecerdasan Buatan ..................................................................................... 11

II.3.1 Definisi Kecerdasan Buatan ................................................................. 11

II.3.2 Soft Computing .................................................................................... 12

II.4 Jaringan Syaraf Tiruan ............................................................................... 12

II.4.1 Definisi Jaringan Syaraf Tiruan ........................................................... 12

II.4.2 Model Jaringan Syaraf Tiruan ............................................................. 14

ix

II.4.3 Arsitektur Jaringan Syaraf Tiruan ........................................................ 15

II.5 Backpropagation ........................................................................................ 17

II.5.1 Definisi Backpropagation .................................................................... 17

II.5.2 Tahap pelatihan Backpropagation ....................................................... 18

II.5.3 Fungsi Aktivasi Backpropagation ....................................................... 19

II.6 Nguyen Widrow .......................................................................................... 20

II.7 Confusion Matriks ...................................................................................... 21

II.7.1 Akurasi ................................................................................................. 22

II.7.2 Sensifititas ............................................................................................ 22

II.7.3 Spesifisitas ........................................................................................... 22

II.7.4 Presisi ................................................................................................... 22

II.7.5 Error Rate ............................................................................................. 23

II.8 Studi Literatur ............................................................................................. 23

BAB III ................................................................................................................. 25

III.1 Kerangka berpikir ...................................................................................... 25

III.1.1 Studi Literatur ..................................................................................... 26

III.1.2 Rumusan Masalah ............................................................................. 26

III.1.3 Pengumpulan Data .............................................................................. 26

III.1.4 Praproses ............................................................................................. 26

III.1.5 Implementasi Algoritma ..................................................................... 26

III.1.6 Perancangan Aplikasi ......................................................................... 26

III.1.7 Pengujian Aplikasi .............................................................................. 27

III.1.8 Laporan ............................................................................................... 27

III.2 Perangkat Penelitian .................................................................................. 27

III.3 Waktu dan Tempat Penelitian ................................................................... 28

III.4 Jadwal Penelitian ....................................................................................... 28

BAB IV ................................................................................................................. 29

IV.1 Akuisisi Data ............................................................................................. 29

IV.2 Praproses Data ......................................................................................... 29

IV.2.1 Data Selection..................................................................................... 29

IV.2.2 Cleaning Data .................................................................................... 30

IV.2.3 Normalisasi ......................................................................................... 31

IV.3 Perancangan Aplikasi ................................................................................ 34

x

IV.3.1UML .................................................................................................... 34

IV.3.2 Perancangan User Interface ................................................................ 37

IV.4 Implementasi Algoritma ........................................................................... 41

IV.4.1 Arsitektur Neural Network ................................................................. 41

IV.4.2 Inisialisasi Bobot ................................................................................ 42

IV.4.3 Tahap Perambatan Maju (Forward-Propagation) ............................. 45

IV.4.4 Tahap Peramban balik (Backpkropagation) ....................................... 46

IV.4.5 Tahap perubahan bobot dan bias ........................................................ 47

IV.4.6 Uji Aplikasi ........................................................................................ 49

IV.4.7 Hasil ................................................................................................... 55

BAB V .................................................................................................................. 56

V.1 Kesimpulan ................................................................................................. 56

V.2 Saran ........................................................................................................... 57

DAFTAR PUSTAKA

Daftar Riwayat Hidup

xi

DAFTAR GAMBAR

Gambar 1 Proses KDD .......................................................................................... 10

Gambar 2 Jaringan Syaraf Tiruan Sederhana ........................................................ 13

Gambar 3 Lapisan dalam JST ............................................................................... 14

Gambar 4 Jaringan berlapis tunggal ...................................................................... 15

Gambar 5 Jaringan Berlapis Ganda ....................................................................... 16

Gambar 6 Jaringan Reccurent ............................................................................... 16

Gambar 7 Arsitektur Backpropagation ................................................................. 17

Gambar 8 Fungsi Aktivasi Sigmoid Biner ............................................................ 19

Gambar 9 Fungsi Aktivasi Sigmoid Bipolar ......................................................... 20

Gambar 10 Kerangka berpikir ............................................................................... 25

Gambar 11 Use Case Diagram .............................................................................. 34

Gambar 12 Activity Diagram ................................................................................ 35

Gambar 13 Sequence Diagram .............................................................................. 36

Gambar 14 Halaman Login ................................................................................... 37

Gambar 15 Halaman Utama .................................................................................. 38

Gambar 16 Halaman Tentang Aplikasi ................................................................. 41

Gambar 17 Contoh Arsitektur Jaringan ................................................................ 42

xii

DAFTAR TABEL

Tabel 1 Confusion Matriks .................................................................................... 21

Tabel 2 Tabel Penelitian ........................................................................................ 23

Tabel 3 Jadwal Penelitian ...................................................................................... 28

Tabel 4 Tabel Atribut ............................................................................................ 29

Tabel 5 Tabel Rekam Medis ................................................................................. 30

Tabel 6 Jumlah Penderita Penyakit Jantung Koroner ........................................... 31

Tabel 7 Tabel Data Pasien yang Sudah di Normalisasi ........................................ 33

Tabel 8 Properti Halaman Login ........................................................................... 37

Tabel 9 Properti Halaman Utama .......................................................................... 39

Tabel 10 Properti Tentang Aplikasi ...................................................................... 41

Tabel 11 Inisiasi Bobot ......................................................................................... 42

Tabel 12 Bobot yang sudah di rubah dengan nguyen ........................................... 43

Tabel 13 Nilai bobot dari lapisan ke output .......................................................... 44

Tabel 14 Tabel Proses Training ............................................................................ 49

Tabel 15 Tabel Hasil Proses Pengujian ................................................................ 52

Tabel 16 Tabel Uji Confussion Matrix ................................................................. 55

xiii

DAFTAR LAMPIRAN

Lampiran 1 Daftar Riwayat Hidup Pakar

Lampiran 2 Data Rekam Medis Pasien Poli Jantung Asli

Lampiran 3 Data Rekam Medis Sudah Di Normalisasi

Lampiran 4 Source Code Login

Lampiran 5 Source Code Halaman Utama

Lampiran 6 Source Code Tentang Aplikasi

Lampiran 7 Tabel Testing Dan Training

Lampiran 8 Backpropagation Tidak Menggunakan Nguyen Widrow

Lampiran 9 Backpropagation Menggunakan Nguyen Widrow

Lampiran 10 Similitary Index Tugas Akhir