International Journal of Mathematics Trends and Technology
Volume 69 | Issue 10 | Year 2023 | Article Id. IJMTT-V69I10P502 | DOI : https://doi.org/10.14445/22315373/IJMTT-V69I10P502
| Received | Revised | Accepted | Published |
|---|---|---|---|
| 15 Aug 2023 | 19 Sep 2023 | 04 Oct 2023 | 26 Oct 2023 |
Bali is a popular destination among domestic and international travellers due to its abundant natural beauty, particularly in tourism. The number of domestic tourists who visited Bali exhibited growth in 2019 but underwent a substantial decrease in 2020 due to the COVID-19 pandemic. Tourism serves as the primary catalyst for economic growth in Bali. This study aims to identify an improved approach to yield precise forecasting outcomes based on available data. The employed techniques encompass the Decomposition and the Holt-Winters methods, which incorporate Additive and Multiplicative models. When comparing the two methods, it is observed that the Holt-Winters Multiplicative method yields the lowest error value for the Mean Absolute Error (MAE), specifically 79866.09, compared to the other ways. The evidence suggests that the Holt-Winters Multiplicative technique outperforms other forecasting methods, as the sample data closely approximates the factual data about the number of trips made by domestic tourists to Bali in 2022. Based on the analysis, it can be inferred that the Holt-Winters Multiplicative method yields more precise outcomes when predicting the volume of domestic tourists in Bali.
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Rado Yendra, Arisman Adnan, Mardani Fitra, Lisa Harianto, Ramadhani Fitri, "A Comparison of the Decomposition Method and the Holt-Winters Method for Forecasting Tourist Visits in Bali," International Journal of Mathematics Trends and Technology (IJMTT), vol. 69, no. 10, pp. 10-16, 2023. Crossref, https://doi.org/10.14445/22315373/IJMTT-V69I10P502
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