Kuliah umum mengenai big data dan data science dan aplikasi nya di dunia nyata

1. YUDY YUNARDY SE, MM
D A N D A T A S C I E N C E

2. DEFINISI
B i g D a t a a d a l a h t e r m i n o l o g i u n t u k
k u m p u l a n d a t a y a n g s a n g a t b e s a r
d a n k o m p l e k s s e h i n g g a c a r a
p e m r o s e s a n s e c a r a t r a d i s i o n a l
t i d a k d a p a t d i l a k u k a n
2

3. 3
DATA
KONVENSIONAL

4. 4
BIG DATA

5. KARAKTERISTIK
BIG DATA
5

6. 6

7. ARSITEKTUR
• DBC1012
• HPCC
• Hadoop (based on MapReduce by Google)
• Mike 2.0
• Multiple layer/distributed parallel
architecture
7

8. TEKNOLOGI
• Machine learning
• Natural Language processing
• Artificial intelligence
8

9. APLIKASI

10. PEMERINTAH
•Sensus penduduk
•Algoritma lampu lalu lintas
•Digital forensic
•Monitor financial market
activity
•Pariwisata
•Pencegahan bencana

11. KESEHATAN
•Penemuan vaksin
•Genom sequence processing
•Contact tracing Covid-19

12. PENDIDIKAN
• Penentuan kurikulum sesuai
kemampuan individu
• Penilaian efektivitas pengajaran,
sehingga tercipta suasana belajar
mengajar yg menyenangkan buat
guru dan murid

13. MEDIA
• Konten yg berbeda untuk
pemirsa yg berbeda
• Rekomendasi konten sesuai
karakteristik individu
• Mengetahui kinerja konten

14. BISNIS
• Penentuan harga yg lebih akurat
per individu
• User experience yg unik untuk
tiap individu
• Mengetahui produk apa yg harus
dijual, kapan dan dimana

15. STUDI KASUS
B a ga i m a n a B i g D a t a
d i g u n a ka n d a l a m b i s n i s
15

16. 16

17. • R e t a i l t e r b e s a r d i d u n i a , 2 j u t a
s t a f d a n 2 0 . 0 0 0 t o k o d i 2 8
N e g a r a
• T h 2 0 0 4 k e t i k a h u r r i c a n e
S a n d y t e r j a d i l o n j a k a n
p e r m i n t a a n t h d l a m p u s e n t e r
d a n s t r a w b e r r y p o p t a r t
• T h 2 0 1 5 m e m b u a t p r i v a t e d a t a
c l o u d y g d p t m e m p r o s e s 2 . 5 P B
i n f o r m a s i p e r j a m
17
LATAR BELAKANG

18. • M e m b e n t u k D a t a C a f é y g
m e n g a n a l i s a 2 0 0 a l i r a n d a t a
i n t e r n a l d a n e x t e r n a l s e c a r a
r e a l t i m e t e r m a s u k 4 0 P B d a t a
t r a n s a k s i m i n g g u s e b e l u m n y a
• S o c i a l g e n o m e p r o j e c t y g
m e m o n i t o r p e r c a k a p a n d i
s o s m e d u n t u k m e m p r e d i k s i
b r g a p a y g a k a n d i b e l i
b e r d a s a r k a n p e r c a k a p a n
m e r e k a
18
BIG DATA DLM
PRAKTEK

19. • M e m p e r s i n g k a t w a k t u
m e n e m u k a n m a s a l a h
s a m p a i m e r u m u s k a n
s o l u s i n y a , d a r i 2 - 3 m i n g g u
m e n j a d i 2 0 m e n i t
19
HASILNYA?

20. • 2 0 0 m i l y a r b a r i s d a t a
t r a n s a k s i b e b e r a p a m i n g g u
t e r a k h i r
• 2 0 0 s u m b e r d a t a l a i n ,
m e t e o r o l o g i , e k o n o m i ,
t e l e k o m , s o c i a l m e d i a , h a r g a
B B M d a n d a t a b a s e k e j a d i a n
t e r k i n i d i s e k i t a r l o k a s i t o k o
20
DATA YG
DIGUNAKAN

21. 21

22. 22
• T i d a k a d a y g d a p a t
m e m p r e d i k s i f i l m a p a y g a k a n
m e n j a d i b o x o f f i c e ( W i l l i a m
G o l d m a n )
• N e t f l i x m e m b u k t i k a n
s e b a l i k n y a , d e n g a n
m e m b a n g u n b i s n i s y g
m e m p r e d i k s i s e c a r a a k u r a t
a p a s a j a y g a k a n m e n j a d i h i t /
e n a k d i t o n t o n
LATAR BELAKANG

23. 23
• M e m i l i k i a n a l i t i k u n t u k
b e r b a g a i b i d a n g ,
p e r s o n a l i z a t i o n , m e s s a g i n g ,
c o n t e n t d e l i v e r y , d e v i c e d l l
• N e t f l i x p r i z e
• S e l a i n a l g o r i t m a , N e t f l i x j u g a
m e n g g u n a k a n t a g g i n g
BIG DATA DLM
PRAKTEK

24. 24
• M e n a m b a h 4 . 9 j u t a p e l a n g g a n
d i Q 1 2 0 1 5 ( d i Q 1 2 0 1 4
m e m i l i k i 4 j u t a p e l a n g g a n )
• P e l a n g g a n N e t f l i x
m e n g h a b i s k a n 1 0 m i l y a r j a m
d i Q 1 2 0 1 5
HASILNYA?

25. 25
• J u d u l k o n t e n , j a m b e r a p a
k o n t e n d i t o n t o n , b e r a p a
w a k t u y g d i h a b i s k a n , s e b e r a p a
s e r i n g k o n t e n d i s t o p / p a u s e
• N e t f l i x j u g a m e n g u m p u l k a n
d a t a t e n t a n g d e l a y y g
d i s e b a b k a n o l e h b u f f e r i n g d a n
b i t r a t e ( y g m e m p e n g a r u h i
k u a l i t a s g a m b a r ) , d a n j u g a
l o k a s i p e l a n g g a n
DATA YG
DIGUNAKAN

26. 26

27. 27
• S o s i a l m e d i a t e r b e s a r d i d u n i a ,
l e b i h d a r i 1 . 5 m i l y a r
p e n g g u n a a k t i f
• 1 0 . 0 0 0 s t a f d i 3 5 n e g a r a
• 2 j u t a p e n g i k l a n a k t i f
LATAR BELAKANG

28. 28
• B e r i k l a n m e n j a d i s a n g a t
a k u r a t d a n e f e k t i f d i f a c e b o o k
• S e l a i n p l a t f o r m u n t u k b e r b a g i
g a m b a r , s u a r a d a n v i d e o j u g a
u n t u k s o f t w a r e
• D a t a p e n g g u n a y g s u d a h b e s a r
d i t a m b a h d g i n s t a g r a m d a n
w h a t s a p p
• M e m p e r s i a p k a n V R s e b a g a i
p l a t f o r m m a s a d e p a n
BIG DATA DLM
PRAKTEK

29. 29
• M e m p e r o l e h p a n g s a p a s a r 2 4 %
d a r i o n l i n e d i s p l a y a d s d i
A m e r i k a ( 2 0 1 4 )
• M e m p e r o l e h p e m a s u k a n 5 . 3
m i l y a r d o l a r d a r i i k l a n ( 2 0 1 4 )
• T h n 2 0 1 7 p a n g s a p a s a r
m e n j a d i 2 7 % d e n g a n
p e m a s u k a n 1 0 m i l y a r d o l a r
HASILNYA?

30. 30
• D a t a a k t i f i t a s p e n g g u n a y g
d i h a s i l k a n s e c a r a o t o m a t i s
( 2 . 5 j u t a k o n t e n t i a p m e n i t )
• M e n g o l a h d a t a i n t e r a k s i
p e n g g u n a t i d a k h a n y a d i d a l a m
f a c e b o o k n a m u n j u g a s i t u s
l a i n ( t e r u t a m a u n t u k k o n t e n
f i l m , m u s i k , b u k u d a n s e r i a l
T V )
DATA YG
DIGUNAKAN

31. 31

32. 32
• S a l a h s a t u s i t u s s o s m e d
t e r t u a d i d u n i a ( d i l u n c u r k a n
2 0 0 3 , f a c e b o o k t h n 2 0 0 4 )
• 4 1 0 j u t a p e n g g u n a d i 2 0 0
n e g a r a
• S e l a l u b e r u s a h a t e t a p r e l e v a n
u n t u k p e n g g u n a p r o f e s i o n a l
y g s i b u k
LATAR BELAKANG

33. 33
• M e r e k a m d a n m e l a c a k s e t i a p
k e g i a t a n p e n g g u n a p d s i t u s
L i n k e d I n
• P e m b e r i a n s a r a n “ p e o p l e y o u
m a y k n o w ” y g a k u r a t b e r k a t
a l g o r i t m a
• S a r a n t s b j u g a m e n c a k u p
t e m a n d a r i t e m a n k i t a
• S a r a n t s b j u g a m e n c a k u p
p e n g g u n a s i t u s l a i n
• M e n g g u n a k a n m a c h i n e
l e a r n i n g a l g o r i t h m
BIG DATA DLM
PRAKTEK

34. 34
• 4 0 j u t a p e n g g u n a b a r u d i
p a r u h p e r t a m a 2 0 1 5
• P e m a s u k a n 7 0 0 j u t a d o l a r
( m e n i n g k a t d a r i 6 4 0 j u t a d o l a r
d i k u a r t a l s e b e l u m n y a )
HASILNYA?

35. 35
• T e k n o l o g i s t r e a m - p r o c e s s i n g ,
d a t a a k t i f i t a s p e n g g u n a d i o l a h
s e c a r a r e a l t i m e
• K o n t e n y g d i l i k e , s h a r e , j e n i s
p e k e r j a a n y g d i k l i k , p e s a n y g
d i k i r i m
• P u l u h a n r i b u s i t u s w e b s e t i a p
d e t i k d i t a m p i l k a n d l m s i t u s
L i n k e d I n j u g a d i p r o s e s
DATA YG
DIGUNAKAN

36. 36
+62

37. T e l k o m s e l m e r u p a k a n s a l a h
s a t u m o b i l e o p e r a t o r y g
m e m i l i k i k e s e r i u s a n t e r h a d a p
B i g D a t a . M e r e k a m e l u n c u r k a n
l a y a n a n B i g D a t a b e r n a m a M -
S i g h t d i t a h u n 2 0 1 4 .
L a y a n a n i n i m e r u p a k a n b a g i a n
d a r i l a y a n a n i k l a n m o b i l e y g
t e r u s a k a n g e n c a r d i t e n g a h
t r e n p e r k e m b a n g a n b i s n i s
d i g i t a l i n i .
37
BAGAIMANA DI
INDONESIA?

38. TERIMA KASIH
Y U D Y Y U N A R D Y
+ 6 2 8 1 1 9 7 7 5 9 5
y u d y.y u n a r d y @ g m a i l . c o m