PERBANDINGAN METODE SEASONAL ARIMA DAN EXTREME LEARNING MACHINE PADA PERAMALAN JUMLAH WISATAWAN MANCANEGARA KE BALI
Abstract
Bali Island of the Gods is one of the wealth of very popular tourist destinations and has the highest number of foreign tourists in Indonesia. It is very necessary to do more in-depth learning related to the projections or forecasting of foreign tourist visits to Bali at a certain period of time. Forecasting analysis used is to compare two methods, namely the Seasonal ARIMA method (SARIMA) and Extreme Learning Machine (ELM). The SARIMA method is a statistical method commonly used in forecasting time series data that contains seasonality and has good accuracy. While the ELM method is a new learning method of artificial neural networks that has fast learning speed and good accuracy. The results obtained indicate that the Seasonal ARIMA method is a better method used to predict the number of tourists to Bali in this case, because it has a smaller forecasting MAPE value of 4.97%. While the ELM method has a forecasting MAPE value of 7.62%.
Downloads
References
A. Assidiq, P. Hendikawati, and N. Dwidayanti, ”Perbandingan Weighted Fuzzy Time Series, Seasonal ARIMA, dan Holt-Winter’s Exponential Smoothing untuk Meramalkan Data Musiman,” UNNES Journal of Mathematics, Vol. 6, No. 2:129-142, 2017.
A. Giusti, A.W. Widodo, and S. Adinugroho, “Prediksi Penjualan Mi Menggunakan Metode Extreme Learning Machine (ELM),” Jurnal Pengembangan Teknologi dan Ilmu Komputer, Vol. 2, No. 8: 2972-2978, Agustus 2018.
A.K. Mishra, and V.R. Desai, “Drought forecasting using stochastic models,” Stoch. Environ. Res. Risk Assess, 19:326–339, Juni 2005.
B.K. Khotimah, E.M. Sari, and H. Yulianarta, “Kinerja Metode Extreme Learning Machine (ELM) pada Sistem Peramalan,” Jurnal SimanteC, Vol. 1, No. 3: 186-191, Desember 2010.
C. Mosabeth, M.T. Furqon, and R.C. Wihandika, ”Prediksi Harga Pasar Daging di Kota Malang dengan menggunakan Metode Extreme Learning Machine,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, Vol. 2, No. 12: 6362-6369, Desember 2018.
D.P. Fardani, E. Wuryanto, and I. Werdiningsih, “Sistem Pendukung Keputusan Peramalan Jumlah Kunjungan Pasien Menggunakan Metode Extreme Learning Machine,” Journal of Information Systems Engineering and Business Intelligence, Vol. 1, No. 1: 33-40, April 2015.
E. Fani, A.W. Widjajati, and Soehardjoepri, “Perbandingan Metode Exponential Smoothing dan Metode Event Based untuk Menentukan Penjualan Produk Terbaik di Perusahaan X,” Jurnal Sains dan Seni ITS, Vol. 6, No. 1: A1-A5, 2017.
F. I. Durrah, Yulia, T.P. Parhusip, and A. Rusyana,“Permalan Jumlah Penumpang di Bandara Sultan Iskandar Muda dengan Metode SARIMA,” Journal of data Analysis, Vol. 1, No. 1: 1-11, Juni 2018.
G.B. Huang, Q.Y. Zhu, and C.K. Siew, “Extreme Learning Machine Theory and Applications,” Neurocomputing, 489-501, Mei 2006.
H.A. Maulana, K.W. Harahap, Adriyansyah, Rofiroh, and F. Zainuddin, “Pemodelan Produksi Kopi Indonesia dengan Menggunakan Seasonal Autoregressive Integrated Moving Average (SARIMA),” Jurnal SAINTIKA UNPAM, Vol. 2, No. 1: 1-14, Juli 2019.
I.N.S. Yasa, I.K.G.D. Putra, and N.M.A.E.D. Wirastuti, ”Peramalan Kurs Rupiah terhadap US Dollar menggunakan Metode Hibrid,” Jurnal Teknologi Elektro, Vol. 16, No. 3: 33-38, Desember 2017.
M.I. Pratama, P.P. Adikara, and S. Adinugroho, “Peramalan Harga Saham Menggunakan Metode Extreme Learning Machine (ELM),” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, Vol. 2, No. 11: 5009-4014, November 2018.
R. Munawaroh, and M.M. Nizam, “Peramalan Wisatawan Mancanegara Ke Provinsi Riau melalui Kota Pekanbaru Menggunakan Metode SARIMA,” Jurnal Sains Matematika dan Statistika, Vol. 2, No. 2: 48-55, Juli 2016.
S.N. Dewi, I.Cholissodin, and E. Santoso, “Prediksi Jumlah Kriminalitas Menggunakan Metode Extreme Learning Machine, ” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, Vol. 2, No. 11:4687-4693, Mei 2018.
V.B. Sitorus, S. Wahyuningsih, and M.N. Hayati, “Peramalan dengan Metode SARIMA di Bidang Ekonomi,” Jurnal EKSPONENSIAL, Vol. 8, No. 1: 17-25, Mei 2017.
W.W.S. Wei, Time Series Analysis Univariate and Multivariate Method 2nd ed, New York (US): Pearson Education, 2006.
Y.A. Sanudin, and J. Nugraha, “Penerapan Metode Extreme Learning Machine untuk Meramalkan Jumlah Wisatawan Mancanegara di Sulawesi Utara,” Jurnal Sendika, Vol. 5, No. 2: 99-109, 2019.
Y. Lohy, ”Peramalan Penerimaan Pajak Hotel dengan Metode Runtun Waktu-ARIMA,” Tesis. Institut Teknologi Sepuluh Nopember, 2017.
Authors who publish with this Journal agree to the following terms:
- Author retain copyright and grant the journal right of first publication with the work simultaneously licensed under a creative commons attribution license that allow others to share the work within an acknowledgement of the work’s authorship and initial publication of this journal.
- Authors are able to enter into separate, additional contractual arrangement for the non-exclusive distribution of the journal’s published version of the work (e.g. acknowledgement of its initial publication in this journal).
- Authors are permitted and encouraged to post their work online (e.g. in institutional repositories or on their websites) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published works.
1.gif)
