data <- read.csv("C:/Users/Ilham Akbar S/Documents/TUGAS/Tugas Kuliah/smstr 4/Anmul/Housing.csv")
head(data)## price area bedrooms bathrooms stories mainroad guestroom basement
## 1 13300000 7420 4 2 3 yes no no
## 2 12250000 8960 4 4 4 yes no no
## 3 12250000 9960 3 2 2 yes no yes
## 4 12215000 7500 4 2 2 yes no yes
## 5 11410000 7420 4 1 2 yes yes yes
## 6 10850000 7500 3 3 1 yes no yes
## hotwaterheating airconditioning parking prefarea furnishingstatus
## 1 no yes 2 yes furnished
## 2 no yes 3 no furnished
## 3 no no 2 yes semi-furnished
## 4 no yes 3 yes furnished
## 5 no yes 2 no furnished
## 6 no yes 2 yes semi-furnishedmengambil data numerik dari dataset
data_numerik <- data[, sapply(data, is.numeric)]
head(data_numerik)## price area bedrooms bathrooms stories parking
## 1 13300000 7420 4 2 3 2
## 2 12250000 8960 4 4 4 3
## 3 12250000 9960 3 2 2 2
## 4 12215000 7500 4 2 2 3
## 5 11410000 7420 4 1 2 2
## 6 10850000 7500 3 3 1 2mengubah ke bentuk matriks
mat <- as.matrix(data_numerik)
head(mat)## price area bedrooms bathrooms stories parking
## [1,] 13300000 7420 4 2 3 2
## [2,] 12250000 8960 4 4 4 3
## [3,] 12250000 9960 3 2 2 2
## [4,] 12215000 7500 4 2 2 3
## [5,] 11410000 7420 4 1 2 2
## [6,] 10850000 7500 3 3 1 2Menghitung Variance-Covariance Matrix
covariance_matrix <- cov(mat)
print("Variance-Covariance Matrix:")## [1] "Variance-Covariance Matrix:"print(covariance_matrix)## price area bedrooms bathrooms stories
## price 3.498544e+12 2.175676e+09 5.059464e+05 4.864093e+05 6.826446e+05
## area 2.175676e+09 4.709512e+06 2.432321e+02 2.113466e+02 1.581294e+02
## bedrooms 5.059464e+05 2.432321e+02 5.447383e-01 1.386738e-01 2.615893e-01
## bathrooms 4.864093e+05 2.113466e+02 1.386738e-01 2.524757e-01 1.421715e-01
## stories 6.826446e+05 1.581294e+02 2.615893e-01 1.421715e-01 7.525432e-01
## parking 6.194673e+05 6.599897e+02 8.856247e-02 7.684161e-02 3.404277e-02
## parking
## price 6.194673e+05
## area 6.599897e+02
## bedrooms 8.856247e-02
## bathrooms 7.684161e-02
## stories 3.404277e-02
## parking 7.423300e-01Menghitung nilai eigen dan vektor eigen
eig <- eigen(covariance_matrix)
print("Nilai Eigen:")## [1] "Nilai Eigen:"print(eig$values)## [1] 3.498546e+12 3.356500e+06 7.345801e-01 5.958731e-01 3.626262e-01
## [6] 1.677009e-01print("Vektor Eigen:")## [1] "Vektor Eigen:"print(eig$vectors)## [,1] [,2] [,3] [,4] [,5]
## [1,] 9.999998e-01 6.218809e-04 2.350022e-07 2.360030e-07 -1.896406e-08
## [2,] 6.218809e-04 -9.999998e-01 -1.068146e-04 4.693651e-05 1.227917e-05
## [3,] 1.446162e-07 2.127405e-05 -4.831235e-01 -3.524835e-01 -7.742078e-01
## [4,] 1.390319e-07 2.715391e-05 -1.156247e-01 -7.418855e-02 -1.559105e-01
## [5,] 1.951224e-07 7.936672e-05 -7.760615e-01 -2.230034e-01 5.897316e-01
## [6,] 1.770643e-07 -8.185750e-05 3.885243e-01 -9.058261e-01 1.688515e-01
## [,6]
## [1,] 1.167426e-07
## [2,] -2.065080e-05
## [3,] 2.072422e-01
## [4,] -9.781712e-01
## [5,] 1.465063e-02
## [6,] -4.137110e-03Menghitung korelasi antar variabel
cor_matrix <- cor(mat)
print("Correlation Matrix:")## [1] "Correlation Matrix:"print(cor_matrix)## price area bedrooms bathrooms stories parking
## price 1.0000000 0.53599735 0.3664940 0.5175453 0.42071237 0.38439365
## area 0.5359973 1.00000000 0.1518585 0.1938195 0.08399605 0.35298048
## bedrooms 0.3664940 0.15185849 1.0000000 0.3739302 0.40856424 0.13926990
## bathrooms 0.5175453 0.19381953 0.3739302 1.0000000 0.32616471 0.17749582
## stories 0.4207124 0.08399605 0.4085642 0.3261647 1.00000000 0.04554709
## parking 0.3843936 0.35298048 0.1392699 0.1774958 0.04554709 1.00000000