PROJECT

library(rpart)
library(rpart.plot)

# 1. Install dan load package
install.packages("rpart")

## Warning: package 'rpart' is in use and will not be installed

install.packages("rpart.plot")

## Warning: package 'rpart.plot' is in use and will not be installed

library(rpart)
library(rpart.plot)

# 2. Buat data simulasi
data <- data.frame(
  Usia = c(25, 32, 45, 60, 28, 50, 35, 55, 40, 30),
  BeratBadan = c(55, 65, 85, 90, 60, 70, 68, 78, 72, 59)
)
# Menampilkan tabel di Console
print(data)

##    Usia BeratBadan
## 1    25         55
## 2    32         65
## 3    45         85
## 4    60         90
## 5    28         60
## 6    50         70
## 7    35         68
## 8    55         78
## 9    40         72
## 10   30         59

# 3. Ubah logika Risiko agar kedua variabel digunakan
# Risiko Tinggi hanya jika Usia ≥ 50 **dan** BeratBadan ≥ 75
data$Risiko <- ifelse(data$Usia >= 50 & data$BeratBadan >= 75, "Tinggi", "Rendah")
data$Risiko <- as.factor(data$Risiko)

# 4. Buat decision tree
tree_model <- rpart(Risiko ~ Usia + BeratBadan, 
                    data = data, 
                    method = "class",
                    control = rpart.control(minsplit = 2, cp = 0.001, maxdepth = 3))

# 5. Gambar pohon keputusan vertikal
rpart.plot(tree_model, 
           type = 2,          # tampilkan aturan dan keputusan
           extra = 104,       # tampilkan jumlah dan proporsi kelas
           under = TRUE,      # letakkan nama kelas di bawah node
           faclen = 0,        # tampilkan label kategori lengkap
           box.palette = "BuGn", # kombinasi warna biru-hijau
           fallen.leaves = TRUE,
           main = "Pohon Keputusan Risiko (Usia & Berat Badan)")