Perbandingan SARIMA dan Dekomposisi pada Peramalan Wisatawan Mancanegara di Sumatera Barat
DOI:
https://doi.org/10.30983/lattice.v5i2.10290Keywords:
Pariwisata, SARIMA, Korespondensi, Time SeriesAbstract
Tourism is a major driver of global economic growth, contributing over 10% of world GDP and generating employment for millions. West Sumatra, Indonesia, offers outstanding natural scenery and rich culture, but international tourist arrivals remain volatile. In January 2024, arrivals reached 4,689, increased to 7,107 in May 2024, and then dropped to 4,631 in June 2024. This variability makes dependable forecasting essential for tourism planning, including promotional programs, service capacity, and destination management. The projections can also support marketing targets, budget allocation, and infrastructure readiness for better policy decisions. This study forecasts international tourist arrivals to West Sumatra using two time-series approaches: Seasonal Autoregressive Integrated Moving Average (SARIMA) and a decomposition method. The best model is selected using Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE). Monthly data are taken from Statistics Indonesia (BPS) for West Sumatra covering January 2010 to December 2024. Results show SARIMA is more accurate, with a MAPE of 1.91%, while decomposition yields 15%. Forecasts for 2025 indicate a peak in September at 10,686 visitors and a trough in March at 5,430 visitors.
Pariwisata merupakan motor penting ekonomi global karena menyumbang lebih dari 10% PDB dunia serta menciptakan lapangan kerja bagi jutaan orang. Provinsi Sumatera Barat memiliki daya tarik alam dan budaya yang kuat, namun kunjungan wisatawan mancanegara masih berfluktuasi. Pada Januari 2024 tercatat 4.689 kunjungan, meningkat hingga 7.107 pada Mei 2024, kemudian turun lagi menjadi 4.631 pada Juni 2024. Fluktuasi ini menuntut peramalan yang andal agar pemerintah dan pelaku usaha dapat menyusun program promosi, kapasitas layanan, dan pengelolaan destinasi secara tepat. Temuan ini dapat membantu penentuan target pemasaran, alokasi anggaran, dan kesiapan infrastruktur pariwisata daerah. Penelitian ini memprediksi jumlah kunjungan wisatawan mancanegara ke Sumatera Barat menggunakan dua metode deret waktu, yaitu Seasonal Autoregressive Integrated Moving Average (SARIMA) dan metode dekomposisi, lalu membandingkan kinerja model berdasarkan Mean Absolute Percentage Error (MAPE) dan Root Mean Squared Error (RMSE). Data berasal dari Badan Pusat Statistik Sumatera Barat periode Januari 2010–Desember 2024. Hasilnya, SARIMA lebih akurat dengan MAPE 1,91% dibanding dekomposisi 15%. Prediksi 2025 menunjukkan puncak pada September 10.686 wisatawan dan terendah pada Maret 5.430 wisatawan.
References
M. R. Ramadhan and J. Nugraha, “Analisis Peramalan Jumlah Kedatangan Pesawat Internasional di Bandar Udara Soekarno-Hatta dengan Menggunakan Metode Dekomposisi-Arima,” Emerging Statistics and Data Science Journal, pp. 159–169, 2023.
M. I. Rizki and T. A. Taqiyyuddin, “). Penerapan model SARIMA untuk memprediksi tingkat inflasi di Indonesia,” Jurnal Sains Matematika dan Statistika, pp. 62–72, 2021.
W. W. S. Wei, . TimeSeries Analysis Univariate and Multivariate Methode Second Edition. Pearson Eddison Wesley., 2006.
S. Makridakis and S. C. Wheelwright, Forecasting Methods and Applications. Wiley, 1998.
W. W. S. Wei, TimeSeries Analysis Univariate and Multivariate Methode Second Edition. Canada: Pearson Eddison Wesley, 2006.
W. Y. Rusyida, Teknik Peramalan: Metode ARIMA dan Holt Winter. NEM.
P. J. Brockwell and R. A. & Davis, Introduction to Time Series and Forecasting (3rd ed.). Springer, 2016.
A. Aswi and A. Sukarna, Analisis Deret Waktu. Bandung. ITB, 2006.
R. S. Al-Gounmeein and M. T. Ismail, “Forecasting the exchange rate of the Jordanian dinar versus the US dollar using a Box-Jenkins seasonal ARIMA model,” School of Mathematical Sciences, Universiti Sains Malaysia., 2019.
D. N. Gujarati and D. C. Porter, Basic Econometrics (5th ed.). New York: McGraw-Hill., 2009.
R. Utami and M. W. I. Maulana, “Visualisasi prediksi kunjungan wisatawan mancanegara menggunakan model time series,” Institut Teknologi Adhi Tama Surabaya, 2020.
I. Ardiansah, I. F. Adiarsa, S. H. Putri, and T. Pujianto, “Penerapan analisis runtun waktu pada peramalan penjualan produk organik menggunakan metode moving average dan exponential smoothing,” Jurnal Teknologi Industri Pertanian, pp. 548–559, 2021.
S. , T. M. W. Yuni and Y. A. Lesnussa, “Peramalan jumlah pengunjung perpustakaan Universitas Pattimura Ambon menggunakan metode dekomposisi,” . Jurusan Matematika, FMIPA Universitas Pattimura., 2020.
D. A. Kristiyanti and Y. Sumarno, “Penerapan metode multiplicative decomposition (seasonal) untuk peramalan persediaan barang pada PT. Agrinusa Jaya Santosa,” Jurnal Sistem Komputer dan Kecerdasan Buatan, 2020.
F. C. Kadoena Rais and L. Handayani, “Metode dekomposisi multiplicatif rata-rata bergerak untuk peramalan tingkat produksi padi ladang Sulawesi Tengah,” Program Studi Statistika, Universitas Tadulako., 2019.
Downloads
Published
How to Cite
Issue
Section
Citation Check
License
Copyright (c) 2025 Rosi Ramayanti, Harifa Hananti, Nur Khasanah, Beni Gusman4
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with Lattice Journal : Journal of Mathematics Education and Applied agree to the following terms: Authors retain copyright and grant the Lattice Journal : Journal of Mathematics Education and Applied right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material) the work for any purpose, even commercially with an acknowledgement of the work's authorship and initial publication in Lattice Journal : Journal of Mathematics Education and Applied. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in Lattice Journal : Journal of Mathematics Education and Applied. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
