IMPLEMENTATION OF DOUBLE EXPONENTIAL SMOOTHING WITH DAMPED PARAMETERS IN THE ESTIMATION OF SOUTH TAPANULI TOURISTS
DOI:
https://doi.org/10.37010/int.v5i2.1790Keywords:
estimation, travelers, double exponential smoothing, damped parametersAbstract
Indonesia is known as a country with many natural and man-made tourist destinations, especially the South Tapanuli region which has marine, natural and man-made tourist destinations that are attractive and worth visiting for domestic and foreign tourists. In 2023, the number of tourists visiting South Tapanuli will be 422,688 people. This research aims to estimate or predict the number of tourists visiting South Tapanuli in the next 6 years using the Double Exponential Smoothing (DES) method with amortized parameters. Double exponential smoothing (DES) is a forecasting method by predicting time series data with a trend model. To overcome overprediction, an attenuating parameter is added which can reduce the estimated value exponentially. This research also aims to compare the estimated number of tourists in South Tapanuli Regency using the T test. This research shows that the estimated number of tourists coming to South Tapanuli Regency in the next six years will increase. For the t test carried out, the results obtained were tcount < ttable (2.014 < 2.015).
References
Anggrismono, A., & Aviva, L. A. M. R. (2023). Dampak sektor pariwisata terhadap pendapatan asli daerah kabupaten/kota di Jawa Tengah. Jurnal Ekonomi Pembangunan STIE Muhammadiyah Palopo, 9(1), 83-93.
Gasperz, V. (2008). Production planning and inventory control. PT Gramedia Pustaka Utama.
Hakimah, M., Rahmawati, W. M., & Afandi, A. Y. (2020). Pengukuran kinerja metode peramalan tipe exponential smoothing dalam parameter terbaiknya. Network Engineering Research Operation, 5(1), 44-50.
Herjanto, E. (2007). Manajemen operasi (Edisi ketiga). Grasindo.
Hudiyanti, C. V., Bachtia, A., & Setiawan, B. D. (2019). Perbandingan double moving average dan double exponential smoothing untuk peramalan jumlah kedatangan wisatawan mancanegara di Bandara Ngurah Rai. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2667-2672.
Lin, C. J., Chen, H. F., & Lee, T. S. (2011). Forecasting tourism demand using time series, artificial neural networks, and multivariate adaptive regression splines: Evidence from Taiwan. International Journal of Business Administration, 2(2), 14-24.
Maliberan, R. M. E. (2019). Forecasting tourist arrival in the province of Surigao del sur, Philippines using time series analysis. JOIV: International Journal on Informatics Visualization, 3(3), 255-261.
Ningsih, P., Maiyastri, M., & Asdi, Y. (2019). Peramalan jumlah kedatangan wisatawan mancanegara ke Sumatera Barat melalui Bandara Internasional Minangkabau dengan model SARIMA. Jurnal Matematika UNAND, 8(2), 128-134.
Nurhasanah, D., Salsabila, A. M., & Kartikasari, M. D. (2022). Forecasting international tourist arrivals in Indonesia using SARIMA model. Enthusiastic: International Journal of Applied Statistics and Data Science, 19-25.
Pitana, I. G., & Gayatri, P. G. (2005). Sosiologi pariwisata. C.V. Andi Offset.
Pratiwi, W. A. (n.d.). Penerapan metode eksponential smoothing dalam memprediksi hasil pencapaian kinerja pelayanan perangkat daerah Dinas Pendidikan Provinsi Riau. Indonesian Council of Premier Statistical Science, 1(1).
Sari, M. A. N., Sumarjaya, I. W., & Susilawati, M. (2019). Peramalan jumlah kunjungan wisatawan mancanegara ke Bali menggunakan metode singular spectrum analysis. E-Jurnal Matematika, 8(4), 303-308.
Sugiyono, P. D. (2020). Metode penelitian kualitatif untuk penelitian yang bersifat: Eksploratif, interpretif dan konstruktif (Y. Suryandari, Ed.). ALFABETA.
Supratanto, J. (1977). Statistik teori dan aplikasi. Erlangga.
Thira, I. J., Mayangky, N. A., Kholifah, D. N., Balla, I., & Gata, W. (2019). Peramalan data kunjungan wisatawan mancanegara ke Indonesia menggunakan fuzzy time series. J. Edukasi dan Penelit. Inform, 5(1).
Warpani, S. P. (2007). Pariwisata dalam tata ruang wilayah. ITB.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 INTELEKTIUM

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The copyright of the received article shall be assigned to the journal as the publisher of the journal. The intended copyright includes the right to publish the article in various forms (including reprints). The journal maintains the publishing rights to the published articles.
INTELEKTIUM Journal is licensed under a Creative Commons — Attribution-NonCommercial-NoDerivatives 4.0 International — CC BY-NC-ND 4.0