Buat data frame

data <- data.frame( Gender = c(1,0,0,1,1), Age = c(30.83, 58.67, 24.50, 27.83, 20.17), Debt = c(0.000, 4.460, 0.500, 1.540, 5.625), Married = c(1,1,1,1,1), BankCustomer = c(1,1,1,1,1), Industry = c(‘Industrials’, ‘Materials’, ‘Materials’, ‘Industrials’, ‘Industrials’), YearsEmployed = c(1.25, 3.04, 1.50, 3.75, 1.71), PriorDefault = c(1,1,1,1,1), Employed = c(1,1,0,1,0), CreditScore = c(1, 6, 0, 5, 0), DriversLicense= c(0,0,0,1,0), Citizen = c(‘ByBirth’, ‘ByBirth’,‘ByBirth’,‘ByBirth’,‘ByOtherMeans’), ZipCode = c(202, 43, 280, 100, 120), Income = c(0, 560, 824, 3, 0), Approved = c(1,1,1,1,1)) print(data)

data\(Industry <- as.numeric(factor(data\)Industry, levels = unique(data\(Industry))) data\)Citizen <- as.numeric(factor(data\(Citizen, levels = unique(data\)Citizen))) print(data)

#htg cov matrix cov_matrix <- cov(data) # Eigen Value & Eigen Vector eigen_result <- eigen(cov_matrix) print(“Eigen Values:”) print(eigen_result\(values) print("Eigen Vector:") print(eigen_result\)vectors)

Var-Covar Matrix

var_cov_matrix <- cov(data) print(“Variance-Covariance Matrix:”) print(var_cov_matrix)

cek standar deviasi tiap kolom

sd_values <- apply(data, 2, sd) print(sd_values)

hapus kolom dengan standar deviasi nol

data_clean <- data[, sd_values > 0] print(“Data setelah menghapus kolom dengan standar deviasi nol:”) print(data_clean)

correlation matrix

cor_matrix <- cor(data_clean) print(“Correlation Matrix:”) print(cor_matrix)