PRAK-PERT-3.R

#Latihan 1
# PACKAGES
library(ggplot2)
library(reshape2)

# DATA
data <- datasets::mtcars

# Memilih variabel
data_mtcars <- data[, c("mpg", "disp", "hp", "wt", "qsec")]

# Matriks Korelasi
cor_mtcars <- cor(data_mtcars)
cor_mtcars

##             mpg       disp         hp         wt       qsec
## mpg   1.0000000 -0.8475514 -0.7761684 -0.8676594  0.4186840
## disp -0.8475514  1.0000000  0.7909486  0.8879799 -0.4336979
## hp   -0.7761684  0.7909486  1.0000000  0.6587479 -0.7082234
## wt   -0.8676594  0.8879799  0.6587479  1.0000000 -0.1747159
## qsec  0.4186840 -0.4336979 -0.7082234 -0.1747159  1.0000000

# Heatmap
data_cor <- melt(cor_mtcars)

ggplot(data_cor, aes(Var1, Var2, fill = value)) +
  geom_tile(color = "black") +
  geom_text(aes(label = round(value, 2)), color = "black") +
  scale_fill_gradient2(
    low = "red",
    high = "green",
    mid = "yellow",
    midpoint = 0,
    limit = c(-1, 1),
    name = "Korelasi"
  ) +
  theme_minimal() +
  labs(
    title = "Heatmap Dataset mtcars",
    x = "Variabel 1",
    y = "Variabel 2"
  ) +
  theme(
    plot.title = element_text(hjust = 0.5),
    axis.text.x = element_text(hjust = 0.5)
  )

#Latihan 2
bern<-function(x,p){p^x*(1-p)^(1-x)}  
bern(1,3/6) 

## [1] 0.5

#Latihan 3
cmfbinom <- function(k, n, p) {  
  # Validasi Input  
  if (k < 0 || n < 0 || p < 0 || p > 1) { 
    stop("Input Tidak Valid")  
  }  
  # Inisialisasi CMF    
  cmf <- 0  
  # Menghitung CMF    
  for (x in 0:k) {  
    prob <- choose(n, x) * (p^x) * ((1 - p)^(n - x))   
    cmf <- cmf + prob  
  }     
  return(cmf)  
}  
# Peluang paling sedikit 2 orang sembuh = 1 - P(X ≤ 1) 
Peluang = 1 - cmfbinom(1, 12, 0.2)   
Peluang

## [1] 0.7251221

#Latihan 4
cmfpois <- function(x, lambda) {    
  if (lambda <= 0) {  
    stop("Lambda Harus Bernilai > 0")  
  }  
  if (x < 0) {      
    return(0)  
  }       
  cmf <- 0    
  for (k in 0:x) {  
    cmf <- cmf + (exp(-lambda) * (lambda^k) / factorial(k))  
  }  
  return(cmf)  
}  
Peluang2 <- cmfpois(10, 2) - cmfpois(0, 2)  
Peluang2

## [1] 0.8646564

#Latihan 5
geo<-function(x,p){p*(1-p)^(x-1)}  
geo(5,0.3)

## [1] 0.07203

#Latihan 6
hyper<-function(x,N,n,k){(((factorial(k)/(factorial(k-
x)*factorial(x)))*(factorial(N-k)/((factorial((N-k)-(n-
x)))*(factorial(n-x)))))/(factorial(N)/(factorial(N-
n)*factorial(n))))}  
hyper(2,100,10,5) 

## [1] 0.07021881