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This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

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summary(cars)
##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

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# Install dan panggil library yang dibutuhkan
if (!requireNamespace("readr", quietly = TRUE)) install.packages("readr")
if (!requireNamespace("dplyr", quietly = TRUE)) install.packages("dplyr")
if (!requireNamespace("knitr", quietly = TRUE)) install.packages("knitr")

library(readr)
library(dplyr)
library(knitr)

# Membaca file CSV dan memilih kolom numerik
data_numeric <- read_csv("data rumah.csv") |> 
                select(where(is.numeric))

# Menghitung eigen values dan eigen vectors dari matriks kovarians
cov_matrix <- cov(data_numeric)
eig <- eigen(cov_matrix)

# Menampilkan hasil dalam format tabel
cat("### Eigenvalues\n")
## ### Eigenvalues
kable(as.data.frame(eig$values), col.names = "Eigenvalues")
Eigenvalues
3.498546e+12
3.356500e+06
7.345801e-01
5.958731e-01
3.626262e-01
1.677009e-01 
cat("### Eigenvectors\n")
## ### Eigenvectors
kable(as.data.frame(eig$vectors))
V1 V2 V3 V4 V5 V6
0.9999998 0.0006219 0.0000002 0.0000002 0.0000000 0.0000001
0.0006219 -0.9999998 -0.0001068 0.0000469 0.0000123 -0.0000207
0.0000001 0.0000213 -0.4831235 -0.3524835 -0.7742078 0.2072422
0.0000001 0.0000272 -0.1156247 -0.0741885 -0.1559105 -0.9781712
0.0000002 0.0000794 -0.7760615 -0.2230034 0.5897316 0.0146506
0.0000002 -0.0000819 0.3885243 -0.9058261 0.1688515 -0.0041371 
cat("### Variance-Covariance Matrix\n")
## ### Variance-Covariance Matrix
kable(as.data.frame(cov_matrix))
price area bedrooms bathrooms stories parking
price 3.498544e+12 2.175676e+09 5.059464e+05 4.864093e+05 6.826446e+05 6.194673e+05
area 2.175676e+09 4.709512e+06 2.432321e+02 2.113466e+02 1.581294e+02 6.599897e+02
bedrooms 5.059464e+05 2.432321e+02 5.447383e-01 1.386738e-01 2.615893e-01 8.856250e-02
bathrooms 4.864093e+05 2.113466e+02 1.386738e-01 2.524757e-01 1.421715e-01 7.684160e-02
stories 6.826446e+05 1.581294e+02 2.615893e-01 1.421715e-01 7.525432e-01 3.404280e-02
parking 6.194673e+05 6.599897e+02 8.856250e-02 7.684160e-02 3.404280e-02 7.423300e-01 
cat("### Correlation Matrix\n")
## ### Correlation Matrix
kable(as.data.frame(cor(data_numeric)))
price area bedrooms bathrooms stories parking
price 1.0000000 0.5359973 0.3664940 0.5175453 0.4207124 0.3843936
area 0.5359973 1.0000000 0.1518585 0.1938195 0.0839961 0.3529805
bedrooms 0.3664940 0.1518585 1.0000000 0.3739302 0.4085642 0.1392699
bathrooms 0.5175453 0.1938195 0.3739302 1.0000000 0.3261647 0.1774958
stories 0.4207124 0.0839961 0.4085642 0.3261647 1.0000000 0.0455471
parking 0.3843936 0.3529805 0.1392699 0.1774958 0.0455471 1.0000000