Forecasting Energy Use Indonesia

# Memuat Library yang diperlukan
library(forecast)
## Warning: package 'forecast' was built under R version 4.3.2
## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo
# Data penggunaan Energy di Indonesia 2004 Sampai 2015
energy <- c(781.802, 785.675, 793.773, 779.737, 784.877, 837.709, 869.232, 826.826, 847.172, 858.805, 880.121, 880.121)

# Mengubah Data Menjadi Seri Waktu
seri_waktu <- ts(energy, start = 2004, end = 2015, frequency = 1)

# Memodelkan Data dengan ARIMA
model_arima <- auto.arima(seri_waktu)

# Melakukan Prediksi untuk 10 tahun kedepan
prediksi <- forecast(model_arima, h = 10)

# Menampilkan Hasil Prediksi
print(prediksi)
##      Point Forecast    Lo 80    Hi 80    Lo 95     Hi 95
## 2016        880.121 848.0439 912.1981 831.0633  929.1787
## 2017        880.121 834.7571 925.4849 810.7429  949.4991
## 2018        880.121 824.5618 935.6802 795.1505  965.0915
## 2019        880.121 815.9667 944.2753 782.0055  978.2365
## 2020        880.121 808.3944 951.8476 770.4246  989.8174
## 2021        880.121 801.5484 958.6936 759.9546 1000.2874
## 2022        880.121 795.2529 964.9891 750.3264 1009.9156
## 2023        880.121 789.3932 970.8488 741.3648 1018.8772
## 2024        880.121 783.8896 976.3524 732.9478 1027.2942
## 2025        880.121 778.6842 981.5578 724.9868 1035.2552
plot(prediksi)

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