Pertemuan 9 SVM

library(mlbench)

## Warning: package 'mlbench' was built under R version 4.4.3

library(e1071)

## Warning: package 'e1071' was built under R version 4.4.3

library(class)

## Warning: package 'class' was built under R version 4.4.3

library(rpart)

## Warning: package 'rpart' was built under R version 4.4.3

library(caret)

## Warning: package 'caret' was built under R version 4.4.3

## Loading required package: ggplot2

## Loading required package: lattice

library(gridExtra)

## Warning: package 'gridExtra' was built under R version 4.4.3

data(PimaIndiansDiabetes)
df <- PimaIndiansDiabetes
set.seed(42)
index <- createDataPartition(df$diabetes, p = 0.7, list = FALSE)
train <- df[index, ]
test <- df[-index, ]

svm_model <- svm(diabetes ~ ., data = train, kernel = "radial")
svm_pred <- predict(svm_model, newdata = test)
svm_acc <- mean(svm_pred == test$diabetes)

knn_pred <- knn(train = train[, -9], test = test[, -9],
                cl = train$diabetes, k = 5)
knn_acc <- mean(knn_pred == test$diabetes)

dt_model <- rpart(diabetes ~ ., data = train, method = "class")
dt_pred <- predict(dt_model, test, type = "class")
dt_acc <- mean(dt_pred == test$diabetes)

cat("Akurasi SVM         :", round(svm_acc * 100, 2), "%\n")

## Akurasi SVM         : 76.09 %

cat("Akurasi KNN (k = 5) :", round(knn_acc * 100, 2), "%\n")

## Akurasi KNN (k = 5) : 70 %

cat("Akurasi Decision Tree:", round(dt_acc * 100, 2), "%\n")

## Akurasi Decision Tree: 73.91 %

library(ggplot2)
library(gridExtra)

results <- data.frame(
  Actual = test$diabetes,
  SVM = svm_pred,
  KNN = knn_pred,
  DecisionTree = dt_pred
)

results$Actual <- factor(results$Actual, levels = c("neg", "pos"))
results$SVM <- factor(results$SVM, levels = c("neg", "pos"))
results$KNN <- factor(results$KNN, levels = c("neg", "pos"))
results$DecisionTree <- factor(results$DecisionTree, levels = c("neg", "pos"))

svm_plot <- ggplot(results, aes(x = Actual, fill = SVM)) +
  geom_bar(position = "dodge") +
  geom_text(stat = "count", aes(label = ..count..), position = position_dodge(0.8), vjust = -0.5) +
  labs(title = "Prediksi SVM", x = "Aktual", y = "Frekuensi") +
  scale_fill_manual(values = c("red", "blue"))

knn_plot <- ggplot(results, aes(x = Actual, fill = KNN)) +
  geom_bar(position = "dodge") +
  geom_text(stat = "count", aes(label = ..count..), position = position_dodge(0.8), vjust = -0.5) +
  labs(title = "Prediksi KNN (k = 5)", x = "Aktual", y = "Frekuensi") +
  scale_fill_manual(values = c("red", "blue"))

dt_plot <- ggplot(results, aes(x = Actual, fill = DecisionTree)) +
  geom_bar(position = "dodge") +
  geom_text(stat = "count", aes(label = ..count..), position = position_dodge(0.8), vjust = -0.5) +
  labs(title = "Prediksi Decision Tree", x = "Aktual", y = "Frekuensi") +
  scale_fill_manual(values = c("red", "blue"))

grid.arrange(svm_plot, knn_plot, dt_plot, ncol = 3)

## Warning: The dot-dot notation (`..count..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(count)` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.