Objek di R

Vektor

Assign

a1 <- c(2,4,7,3)
a1

## [1] 2 4 7 3

assign("a2",c("2","4","7","3"))
a2

## [1] "2" "4" "7" "3"

Baris Bilangan

a3 <- seq(1,10,by=0.5)
a3

##  [1]  1.0  1.5  2.0  2.5  3.0  3.5  4.0  4.5  5.0  5.5  6.0  6.5  7.0  7.5  8.0
## [16]  8.5  9.0  9.5 10.0

a4 <- seq(1,10,length.out=12)
a4

##  [1]  1.000000  1.818182  2.636364  3.454545  4.272727  5.090909  5.909091
##  [8]  6.727273  7.545455  8.363636  9.181818 10.000000

Bilangan Berulang

a5 <- rep(1,3)
a5

## [1] 1 1 1

a6 <- rep(1:3,3)
a6

## [1] 1 2 3 1 2 3 1 2 3

a7 <- rep(1:3,1:3)
a7

## [1] 1 2 2 3 3 3

a8 <- rep(1:3,rep(2,3))
a8

## [1] 1 1 2 2 3 3

a9 <- rep(1:3,each=2)
a9

## [1] 1 1 2 2 3 3

Karakter Berpola

a10 <- paste("A",1:10,sep="")
a10

##  [1] "A1"  "A2"  "A3"  "A4"  "A5"  "A6"  "A7"  "A8"  "A9"  "A10"

a11 <- paste0("A",1:10)
a11

##  [1] "A1"  "A2"  "A3"  "A4"  "A5"  "A6"  "A7"  "A8"  "A9"  "A10"

a12 <- paste("A",1:10,sep="-")
a12

##  [1] "A-1"  "A-2"  "A-3"  "A-4"  "A-5"  "A-6"  "A-7"  "A-8"  "A-9"  "A-10"

a13 <- paste0("A",a8)
a13

## [1] "A1" "A1" "A2" "A2" "A3" "A3"

Akses Vector

a2[3]

## [1] "7"

a3[10:15]

## [1] 5.5 6.0 6.5 7.0 7.5 8.0

a10[c(4,7,9)]

## [1] "A4" "A7" "A9"

a13[-c(1:2)]

## [1] "A2" "A2" "A3" "A3"

length(a4)

## [1] 12

Latihan 1

c("la","ye")[rep(c(1,2,2,1),times=4)]

##  [1] "la" "ye" "ye" "la" "la" "ye" "ye" "la" "la" "ye" "ye" "la" "la" "ye" "ye"
## [16] "la"

c("la","ye")[rep(rep(1:2,each=3),2)]

##  [1] "la" "la" "la" "ye" "ye" "ye" "la" "la" "la" "ye" "ye" "ye"

Latihan 2

X <- paste(c("X", "Y"),1:10,sep="")
X

##  [1] "X1"  "Y2"  "X3"  "Y4"  "X5"  "Y6"  "X7"  "Y8"  "X9"  "Y10"

Respon <- seq(1,28, by = 3)
Respon

##  [1]  1  4  7 10 13 16 19 22 25 28

Matrix

Mendifinisikan Matrix

a14 <- 1:12
a14

##  [1]  1  2  3  4  5  6  7  8  9 10 11 12

b1 <- matrix(a14,3,4)
b1

##      [,1] [,2] [,3] [,4]
## [1,]    1    4    7   10
## [2,]    2    5    8   11
## [3,]    3    6    9   12

b2 <- matrix(a14,3,4,byrow=TRUE)
b2

##      [,1] [,2] [,3] [,4]
## [1,]    1    2    3    4
## [2,]    5    6    7    8
## [3,]    9   10   11   12

b3 <- matrix(1:10,4,4)

## Warning in matrix(1:10, 4, 4): data length [10] is not a sub-multiple or
## multiple of the number of rows [4]

b3

##      [,1] [,2] [,3] [,4]
## [1,]    1    5    9    3
## [2,]    2    6   10    4
## [3,]    3    7    1    5
## [4,]    4    8    2    6

b4 <- matrix(1:10,4,5)
b4

##      [,1] [,2] [,3] [,4] [,5]
## [1,]    1    5    9    3    7
## [2,]    2    6   10    4    8
## [3,]    3    7    1    5    9
## [4,]    4    8    2    6   10

Merubah Objek Vector ke Matrix

b5 <- a14
dim(b5)<-c(6,2) 
b5

##      [,1] [,2]
## [1,]    1    7
## [2,]    2    8
## [3,]    3    9
## [4,]    4   10
## [5,]    5   11
## [6,]    6   12

Membuat Matriks dengan definisi n baris

b6 <- matrix(1:4,2)
b6

##      [,1] [,2]
## [1,]    1    3
## [2,]    2    4

b7 <- matrix(6:9,2)
b7

##      [,1] [,2]
## [1,]    6    8
## [2,]    7    9

Mengabungkan baris

b8 <- rbind(b6,b7)
b8

##      [,1] [,2]
## [1,]    1    3
## [2,]    2    4
## [3,]    6    8
## [4,]    7    9

Mengabungkan kolom

b9 <- cbind(b7,b6) 
b9

##      [,1] [,2] [,3] [,4]
## [1,]    6    8    1    3
## [2,]    7    9    2    4

Melihat Ukuran Matrix

dim(b8)

## [1] 4 2

dim(b9)

## [1] 2 4

dim(a14)

## NULL

length(b3)

## [1] 16

Mengakses matrix

b2

##      [,1] [,2] [,3] [,4]
## [1,]    1    2    3    4
## [2,]    5    6    7    8
## [3,]    9   10   11   12

b2[2,3]

## [1] 7

b2[2,2:4]

## [1] 6 7 8

b2[1:2,]

##      [,1] [,2] [,3] [,4]
## [1,]    1    2    3    4
## [2,]    5    6    7    8

b2[c(1,3),-2]

##      [,1] [,2] [,3]
## [1,]    1    3    4
## [2,]    9   11   12

b2[10]

## [1] 4

Array

Mendifinisikan Array

c1 <- array(a14,dim=c(2,2,3))
c1

## , , 1
## 
##      [,1] [,2]
## [1,]    1    3
## [2,]    2    4
## 
## , , 2
## 
##      [,1] [,2]
## [1,]    5    7
## [2,]    6    8
## 
## , , 3
## 
##      [,1] [,2]
## [1,]    9   11
## [2,]   10   12

c2 <- array(a14,dim=c(2,1,2,3))
c2

## , , 1, 1
## 
##      [,1]
## [1,]    1
## [2,]    2
## 
## , , 2, 1
## 
##      [,1]
## [1,]    3
## [2,]    4
## 
## , , 1, 2
## 
##      [,1]
## [1,]    5
## [2,]    6
## 
## , , 2, 2
## 
##      [,1]
## [1,]    7
## [2,]    8
## 
## , , 1, 3
## 
##      [,1]
## [1,]    9
## [2,]   10
## 
## , , 2, 3
## 
##      [,1]
## [1,]   11
## [2,]   12

c3 <- array(a14,dim=c(1,2,4,2))
c3

## , , 1, 1
## 
##      [,1] [,2]
## [1,]    1    2
## 
## , , 2, 1
## 
##      [,1] [,2]
## [1,]    3    4
## 
## , , 3, 1
## 
##      [,1] [,2]
## [1,]    5    6
## 
## , , 4, 1
## 
##      [,1] [,2]
## [1,]    7    8
## 
## , , 1, 2
## 
##      [,1] [,2]
## [1,]    9   10
## 
## , , 2, 2
## 
##      [,1] [,2]
## [1,]   11   12
## 
## , , 3, 2
## 
##      [,1] [,2]
## [1,]    1    2
## 
## , , 4, 2
## 
##      [,1] [,2]
## [1,]    3    4

c4 <- array(a14,dim=c(3,4))
c4

##      [,1] [,2] [,3] [,4]
## [1,]    1    4    7   10
## [2,]    2    5    8   11
## [3,]    3    6    9   12

Mengakses Array

#lembar 1 dari c2
c2[,,1,]

##      [,1] [,2] [,3]
## [1,]    1    5    9
## [2,]    2    6   10

#buku ke 2 dari c2
c2[,,,2]

##      [,1] [,2]
## [1,]    5    7
## [2,]    6    8

#lembar ke 1 buku ke 3 dari c2
c2[,,1,3]

## [1]  9 10

Factor

Mendefinsikan Factor

#skala pengukuran nominal
a15 <- c("A","B","AB","O")
a15

## [1] "A"  "B"  "AB" "O"

d1 <- factor(a15) 
d1

## [1] A  B  AB O 
## Levels: A AB B O

d2 <- factor(a15,levels=c("O","A","B","AB"))
d2

## [1] A  B  AB O 
## Levels: O A B AB

levels(d2)

## [1] "O"  "A"  "B"  "AB"

a16 <- c("SD","SMP","SMA")
a16

## [1] "SD"  "SMP" "SMA"

#skala pengukuran ordinal
d3 <- ordered(a16) 
d3

## [1] SD  SMP SMA
## Levels: SD < SMA < SMP

d4 <- ordered(a16, levels=a16)
d4

## [1] SD  SMP SMA
## Levels: SD < SMP < SMA

d5 <- factor(a16, levels=a16, ordered=TRUE)
d5

## [1] SD  SMP SMA
## Levels: SD < SMP < SMA

levels(d4)

## [1] "SD"  "SMP" "SMA"

Mengakses factor

d1[2]

## [1] B
## Levels: A AB B O

d4[2:3]

## [1] SMP SMA
## Levels: SD < SMP < SMA

List

Mendefinisikan List

a1; b2; c1; d2

## [1] 2 4 7 3

##      [,1] [,2] [,3] [,4]
## [1,]    1    2    3    4
## [2,]    5    6    7    8
## [3,]    9   10   11   12

## , , 1
## 
##      [,1] [,2]
## [1,]    1    3
## [2,]    2    4
## 
## , , 2
## 
##      [,1] [,2]
## [1,]    5    7
## [2,]    6    8
## 
## , , 3
## 
##      [,1] [,2]
## [1,]    9   11
## [2,]   10   12

## [1] A  B  AB O 
## Levels: O A B AB

e1 <- list(a1,b2,c1,d2)
e2 <- list(vect=a1,mat=b2,array=c1,fac=d2)

Mengakses List

e1[[1]]

## [1] 2 4 7 3

e2$fac

## [1] A  B  AB O 
## Levels: O A B AB

e2[2]

## $mat
##      [,1] [,2] [,3] [,4]
## [1,]    1    2    3    4
## [2,]    5    6    7    8
## [3,]    9   10   11   12

e1[c(2,4)]

## [[1]]
##      [,1] [,2] [,3] [,4]
## [1,]    1    2    3    4
## [2,]    5    6    7    8
## [3,]    9   10   11   12
## 
## [[2]]
## [1] A  B  AB O 
## Levels: O A B AB

dim(e2)

## NULL

length(e2)

## [1] 4

names(e2)

## [1] "vect"  "mat"   "array" "fac"

Data Frame

Mendefinisikan Dataframe

a17 <- 11:15
a17

## [1] 11 12 13 14 15

d5 <- factor(LETTERS[6:10])
d5

## [1] F G H I J
## Levels: F G H I J

f1 <- data.frame(d5,a17)
f1

Mengakses Dataframe

f1[1,2]

## [1] 11

f1[3,]

f1$d5

## [1] F G H I J
## Levels: F G H I J

f1[,"a17"]

## [1] 11 12 13 14 15

colnames(f1)

## [1] "d5"  "a17"

str(f1)

## 'data.frame':    5 obs. of  2 variables:
##  $ d5 : Factor w/ 5 levels "F","G","H","I",..: 1 2 3 4 5
##  $ a17: int  11 12 13 14 15

summary(f1)

##  d5         a17    
##  F:1   Min.   :11  
##  G:1   1st Qu.:12  
##  H:1   Median :13  
##  I:1   Mean   :13  
##  J:1   3rd Qu.:14  
##        Max.   :15

Mengkonfirmasi Jenis Objek Data


Untuk melihat jenis dari objek data dapat menggunakan fungsi berikut :
• is.vector()
• is.matrix()
• is.array()
• is.factor()
• is.list()
• is.data.frame()

is.vector(a1)

## [1] TRUE

is.matrix(b1)

## [1] TRUE

is.array(c1)

## [1] TRUE

is.factor(d1)

## [1] TRUE

is.list(e1)

## [1] TRUE

is.data.frame(f1)

## [1] TRUE

Mengkonfirmasi Jenis Objek Data

Untuk merubah suatu objek data ke objek data lainya yang diperlukan dapat menggunakan fungsi berikut : 
• as.vector()
• as.matrix()
• as.array()
• as.factor()
• as.list()
• as.data.frame()

as.vector(d2)

## [1] "A"  "B"  "AB" "O"

as.matrix(d2)

##      [,1]
## [1,] "A" 
## [2,] "B" 
## [3,] "AB"
## [4,] "O"

as.array(d2)

## [1] A  B  AB O 
## Levels: O A B AB

as.factor(d2)

## [1] A  B  AB O 
## Levels: O A B AB

as.list(d2)

## [[1]]
## [1] A
## Levels: O A B AB
## 
## [[2]]
## [1] B
## Levels: O A B AB
## 
## [[3]]
## [1] AB
## Levels: O A B AB
## 
## [[4]]
## [1] O
## Levels: O A B AB

as.data.frame(d2)

Latihan 3

Seorang peneliti merancang sebuah perancangan percobaan RAKL dengan 4 perlakuan dan 3 kelompok (anggaplah respon percobaan berupa baris bilangan). Bantulah peneliti tersebut untuk membuat raw data seperti output sebagai berikut!

Perl <- paste("P", rep(1:4, each=3), sep = "")
Perl

##  [1] "P1" "P1" "P1" "P2" "P2" "P2" "P3" "P3" "P3" "P4" "P4" "P4"

Kel <- rep(1:3, 4)
Kel

##  [1] 1 2 3 1 2 3 1 2 3 1 2 3

Resp <- seq(1,23, by=2)
Resp

##  [1]  1  3  5  7  9 11 13 15 17 19 21 23

data1 <- data.frame(Perl, Kel, Resp)
data1

Pengolahan Objek dan Struktur Kendali

Operasi aljabar sederhana vektor numerik

x1 <- c(2,6,9,5)
x1

## [1] 2 6 9 5

x2 <- 1:4
x2

## [1] 1 2 3 4

x3 <- x1 + 1:2
x3

## [1]  3  8 10  7

x4 <- x1 + 1:3

## Warning in x1 + 1:3: longer object length is not a multiple of shorter object
## length

x4

## [1]  3  8 12  6

x5 <- x1*x2
x5

## [1]  2 12 27 20

#setara x'x
x6 <- x1 %*% x1  
x6

##      [,1]
## [1,]  146

#setara xx'
x7 <- x1 %o% x1  
x7

##      [,1] [,2] [,3] [,4]
## [1,]    4   12   18   10
## [2,]   12   36   54   30
## [3,]   18   54   81   45
## [4,]   10   30   45   25

Operasi dasar vektor karakter

y1 <- c("Institut Pertanian Bogor")
y1

## [1] "Institut Pertanian Bogor"

n1 <- nchar(y1)
n1

## [1] 24

y2 <- c("Adam","Pramesti","Fathi","Ririn")
y2

## [1] "Adam"     "Pramesti" "Fathi"    "Ririn"

n2 <- nchar(y2)
n2

## [1] 4 8 5 5

y3 <- substr(y1,15,18) 
y3

## [1] "nian"

y4 <- substring(y1,15)
y4

## [1] "nian Bogor"

y5 <- substring(y1,4,8)
y5

## [1] "titut"

Operasi dasar matriks

Z1 <- matrix(1:6,2,3)
Z1

##      [,1] [,2] [,3]
## [1,]    1    3    5
## [2,]    2    4    6

Z2 <- matrix(1:6,3,2,byrow=T)
Z2

##      [,1] [,2]
## [1,]    1    2
## [2,]    3    4
## [3,]    5    6

Z3 <- matrix(6:9,2,2)
Z3

##      [,1] [,2]
## [1,]    6    8
## [2,]    7    9

Z4 <- Z1 %*% Z2
Z4

##      [,1] [,2]
## [1,]   35   44
## [2,]   44   56

Z5 <- Z3 * Z4
Z5

##      [,1] [,2]
## [1,]  210  352
## [2,]  308  504

#invers
INVZ <- solve(Z4) 

#identitas
INVZ %*% Z4

##      [,1]         [,2]
## [1,]    1 2.842171e-14
## [2,]    0 1.000000e+00

h <- c(5,11)
h

## [1]  5 11

#solusi SPL Zp=h
p <- solve(Z4,h) 
p

## [1] -8.500  6.875

#eigen value & eigen vector dr Z4
e <- eigen(Z4) 
e

## eigen() decomposition
## $values
## [1] 90.7354949  0.2645051
## 
## $vectors
##           [,1]       [,2]
## [1,] 0.6196295 -0.7848945
## [2,] 0.7848945  0.6196295

#akses eigen values
e$values

## [1] 90.7354949  0.2645051

#akses eigen vectors
e[[2]]

##           [,1]       [,2]
## [1,] 0.6196295 -0.7848945
## [2,] 0.7848945  0.6196295

Struktur Kendali

for

for (i in 1:5) 
  print(i^2)

## [1] 1
## [1] 4
## [1] 9
## [1] 16
## [1] 25

y=runif(20)
for (i in y) {
if(i<0.5){
print(100*i)
} 
  else print(i/100)
}

## [1] 0.009394539
## [1] 29.31272
## [1] 14.65935
## [1] 0.007485204
## [1] 40.66847
## [1] 0.006261617
## [1] 0.009710735
## [1] 0.005433559
## [1] 17.51551
## [1] 0.00615691
## [1] 0.006573868
## [1] 0.2670769
## [1] 43.41068
## [1] 0.007820979
## [1] 0.009201869
## [1] 24.14625
## [1] 0.009933243
## [1] 0.007723201
## [1] 47.33581
## [1] 48.46751

while

i<-1
while (i<=5) {
print(i^2)
i=i+1
}

## [1] 1
## [1] 4
## [1] 9
## [1] 16
## [1] 25

z=0
while(z<=10) {
y=runif(20)
z=sum(y)
print(z)
}

## [1] 10.75731

switch

acak <- sample(1:5,1)
acak

## [1] 5

switch(EXPR=acak, "1" = "a", "2" = "z",
"3" = "m", "4" = "h", "5" = "t")

## [1] "t"

apply

Z6 <- matrix(1:25,5,5)
Z6

##      [,1] [,2] [,3] [,4] [,5]
## [1,]    1    6   11   16   21
## [2,]    2    7   12   17   22
## [3,]    3    8   13   18   23
## [4,]    4    9   14   19   24
## [5,]    5   10   15   20   25

apply(Z6,1,sum)

## [1] 55 60 65 70 75

apply(Z6,2,sd)

## [1] 1.581139 1.581139 1.581139 1.581139 1.581139

Latihan 1

Tentukan hasil dari setiap perintah berikut

a<-0
for(i in 1:5)
{ b<-a+i
print(b)
a<-b
}

## [1] 1
## [1] 3
## [1] 6
## [1] 10
## [1] 15

i<-1
z<-1
while(z<15)
{ y<-z+i
z<-y
print(z)
i<-i+1
}

## [1] 2
## [1] 4
## [1] 7
## [1] 11
## [1] 16

i<-1
m<-2
repeat
{ m<-m+i
print(m)
i<-i+1
if(m>15)
break
}

## [1] 3
## [1] 5
## [1] 8
## [1] 12
## [1] 17

LAPORAN RESPONSI 02 PEMROGRAMAN STATISTIKA - STA 561

Nur Hikmah / G1501211023

2021-09-15

Objek di R

Vektor

Assign

Baris Bilangan

Bilangan Berulang

Karakter Berpola

Akses Vector

Latihan 1

Latihan 2

Matrix

Mendifinisikan Matrix

Merubah Objek Vector ke Matrix

Membuat Matriks dengan definisi n baris

Mengabungkan baris

Mengabungkan kolom

Melihat Ukuran Matrix

Mengakses matrix

Array

Mendifinisikan Array

Mengakses Array

Factor

Mendefinsikan Factor

Mengakses factor

List

Mendefinisikan List

Mengakses List

Data Frame

Mendefinisikan Dataframe

Mengakses Dataframe

Mengkonfirmasi Jenis Objek Data

Mengkonfirmasi Jenis Objek Data

Latihan 3

Pengolahan Objek dan Struktur Kendali

Operasi aljabar sederhana vektor numerik

Operasi dasar vektor karakter

Operasi dasar matriks

Struktur Kendali

for

while

switch

apply

Latihan 1