Pendekatan Percentile Error Bootstrap pada Model Double Seasonal Holt-Winters, Double Seasonal ARIMA, dan Naïve untuk Peramalan Beban Listrik Jangka Pendek Area Jawa Timur-Bali

Hidayatul Khusna, Suhartono Suhartono
Submission Date: 2015-02-02 15:08:49
Accepted Date: 2015-03-16 09:16:43

Abstract


Interval prediksi pada model double seasonal Holt-Winters (DSHW) tidak dapat dikonstruksi dengan cara analitis. Jika digunakan untuk meramal jauh ke depan, model double seasonal ARIMA memiliki varians error yang semakin besar sehingga interval prediksi menjadi semakin lebar. Sementara model Naïve untuk data musiman memiliki varians error yang semakin besar setiap kelipatan periode musiman. Penelitian ini bertujuan untuk meramalkan beban listrik area Jawa Timur-Bali menggunakan pendekatan percentile error bootstrap (PEB) pada model DSHW, DSARIMA, dan Naïve. Data yang digunakan adalah beban listrik per setengah jam dalam satuan Mega Watt (MW) dari periode 1 Januari 2013 hingga 30 September 2014. Hasil penelitian menunjukkan bahwa model DSARIMA merupakan model terbaik berdasarkan kriteria out-sample sMAPE, kriteria in-sample AIC-SBC, serta kriteria out-sample rata-rata lebar interval prediksi. Dengan demikian, dapat disimpulkan bahwa model terbaik untuk peramalan beban listrik jangka pendek area Jawa Timur-Bali adalah model DSARIMA dengan interval prediksi yang dikonstruksi menggunakan pendekatan percentile error bootstrap.

Keywords


beban listrik;double seasonal ARIMA;double seasonal Holt-Winters;Naïve;percentile error bootstrap

References


Muchlis, M & Permana, A. D. 2003. Proyeksi Kebutuhan Listrik PLN Tahun 2003 s.d. 2010. Diambil kembali dari website: http://www.oocities.org/markal_bppt/publish/slistrk/slmuch.pdf. diakses pada tanggal 20 September 2014 pada pukul 03.41.

Puspitasari, I. 2011. Model Dua Level Seasonal Autoregressive Hibrida ARIMA-ANFIS Untuk Peramalan Beban Listrik Jangka Pendek Di Jawa Bali. Laporan Tugas Akhir Jurusan Statistika. Surabaya: ITS.

Utomo, P. D. 2012. Penerapan Model DSARFIMA untuk Peramalan Beban Konsumsi Listrik Jangka Pendek di Jawa Timur dan Bali. Laporan Tugas Akhir Jurusan Statistika. Surabaya: ITS.

Taylor, J. W. & McSharry, P. E. 2008. Short-Term Load Forecasting Methods: An Evaluation Based on European Data. IEEE Transactions on Power Systems, 22, 2213-2219.

Hyndman, R. J., Koehler, A. B., Snyder, R. D. & Grose, S. 2002. A State Space Framework for Automatic Forecasting Using Exponential Smoothing Methods. International Journal of Forecasting, 18, 439-454.

Hyndman, R. J. & Fan, S. 2010. Density Forecasting for Long-Term Peak Electricity Demand. IEEE Transaction on Power System, 25(2), 1142-1153.

Lailiya, A. R. 2013. Pendekatan Bootstrap untuk Konstruksi Interval Prediksi pada Model Double Seasonal Holt-Winters. Laporan Tesis Jurusan Statistika. Surabaya: ITS.

Taylor, J. W. 2003. Short-Term Electricity Demand Forecasting Using Double Seasonal Exponential Smoothing. Journal of Operational Research Society, 54, 799-805.

Taylor, J. W. 2010. Triple Seasonal Methods for Short-Term Electricity Demand Forecasting. European Journal of Operational Research, 204, 139-152.

Mohamed, N., Ahmad, M. H., Ismail, Z. & Suhartono. 2010. Double Seasonal ARIMA Model for Forecasting Load Demand. Matematika, 26, 217-231.

Suhartono & Endharta, A. J. 2009. Short Term Electricity Load Demand Forecasting in Indonesia by Using Double Seasonal Recurrent Neural Networks. International Journal of Mathematical Models and Methods In Applied Sciences, 3(3), 171-178.

Hanke, J.E. & Reitsch, A.G. 1995. Business Forecasting (5th Ed.). Prentice Hall.

Boedoyo, M. S. 2006. Perencanaan Kelistrikan dalam Menunjang Pembangunan Nasional yang Berkesinambungan : Sistem Kelistrikan di Jamali Tahun 2003 s.d. Tahun 2020. Terbit 31 Juli 2006.


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