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#Ashila Nasywa Salsabila
#5003221183

set.seed(123)

# Simulasi white noise
n <- 200
at <- rnorm(n + 36, mean = 0, sd = 2)  # Tambah panjang untuk seasonal lag

# Parameter musiman (periode 12)
Phi1 <- 0.5
Phi2 <- -0.4
Phi3 <- 0.3
Theta1 <- 0.6
Theta2 <- -0.5
Theta3 <- 0.4

# Inisialisasi vektor y
y <- numeric(n + 36)
# Diferensiasi musiman: (1 - B^12)
for (t in 37:(n + 36)) {
  y[t] <- (Phi1 * y[t-12]) + (Phi2 * y[t-24]) + (Phi3 * y[t-36]) +
    at[t] + (Theta1 * at[t-12]) + (Theta2 * at[t-24]) + (Theta3 * at[t-36])
}

# Hilangkan bagian awal yang dummy
yt <- y[37:(n + 36)]

# Plot hasil simulasi
ts.plot(yt, main = "Simulasi ARIMA(0,0,0)(3,1,3)[12]", ylab = "y_t", col = "blue")

# Menampilkan grafik ACF dan PACF berdampingan
par(mfrow = c(1, 2))  # 1 baris, 2 kolom

acf(yt, main = "ACF dari Series y")
pacf(yt, main = "PACF dari Series y")

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