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#TUGAS VISUALISASI DAN INTERPRETASI DATA KOMPUTASI STATISTIKA
#NAMA: ALINEA AUFKLARUNG
#NRP: 5003251152
#KELAS: D

library(ggplot2)
library(corrplot)

#Analisis Winzorised Mean
data_awal <- c(12, 45, 52, 58, 61, 63, 67, 70, 72, 75, 78, 82, 88, 95, 310)

winsor_function <- function(data, alpha) {
  data_sort <- sort(data)
  n <- length(data_sort)
  k <- floor(n * alpha)
  winsor_data <- data_sort
  
  if (k > 0) {
    for (i in 1:k) {
      winsor_data[i] <- data_sort[k + 1]
    }
    for (i in (n - k + 1):n) {
      winsor_data[i] <- data_sort[n - k]
    }
  }
  return(winsor_data)
}

# Menghitung data winsorized 20%
data_winsor_20 <- winsor_function(data_awal, 0.2)

# Menampilkan Ringkasan Mean
hasil_mean <- data.frame(
  Metode = c("Ordinary Mean", "Winsorized Mean 20%"),
  Nilai = c(mean(data_awal), mean(data_winsor_20))
)
print(hasil_mean)

               Metode    Nilai
1       Ordinary Mean 81.86667
2 Winsorized Mean 20% 69.73333

#Visualisasi Perbandingan
df_boxplot <- data.frame(
  Nilai = c(data_awal, data_winsor_20),
  Tipe = rep(c("Original", "Winsorized 20%"), each = length(data_awal))
)

ggplot(df_boxplot, aes(x = Tipe, y = Nilai, fill = Tipe)) +
  geom_boxplot(outlier.colour = "red", outlier.shape = 16) +
  scale_fill_manual(values = c("salmon", "lightblue")) +
  labs(title = "Dampak Winsorizing terhadap Pencilan",
       x = "Metode Data", y = "Nilai") +
  theme_minimal()

#Matriks Korelasi Tertimbang
Rw_matrix <- matrix(c(1.0000000, -0.9531095, -0.9558207,
                     -0.9531095,  1.0000000,  0.9891979,
                     -0.9558207,  0.9891979,  1.0000000), 
                   nrow = 3, byrow = TRUE)

colnames(Rw_matrix) <- rownames(Rw_matrix) <- c("x1", "x2", "x3")

# Menampilkan Matriks
print(Rw_matrix)

           x1         x2         x3
x1  1.0000000 -0.9531095 -0.9558207
x2 -0.9531095  1.0000000  0.9891979
x3 -0.9558207  0.9891979  1.0000000

#Visualisasi(Heatmap Korelasi)
corrplot(Rw_matrix, 
         method = "color", 
         addCoef.col = "black", 
         tl.col = "black", 
         title = "Heatmap Korelasi Tertimbang", 
         mar = c(0, 0, 2, 0))

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