Inferensi
Vol 7, No 1 (2024)

Penerapan Metode Hybrid Dekomposisi-Arima dalam Peramalan Jumlah Wisatawan Mancanegara

Aswi Aswi (Universitas Negeri Makassar)
Ina Rahma (Prodi Statistika FMIPA UNM)
Muhammad Fahmuddin (Prodi Statistika FMIPA UNM)



Article Info

Publish Date
25 Mar 2024

Abstract

The Decomposition-ARIMA hybrid method is a combination of two methods used to predict future events in time series data. This method separates the data into three components: the seasonal component, the trend component, and the random component. The decomposition method is employed to forecast the seasonal and the trend components in a data series, while the ARIMA method is utilized to predict the random component within the data series. A tourist is an individual who visits an area for a specific period, making use of its facilities and infrastructure. In order to ascertain the growth of the number of foreign tourists, this study employs the decomposition-ARIMA hybrid method. The aim is to derive forecasting results from the data on the count of foreign tourists from January 2022 to December 2022. The research finding indicates that the best ARIMA model is ARIMA (0, 1, 1) with a Mean Absolute Percentage Error (MAPE) of 8.5% signifying a very high forecast accuracy.

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Journal Info

Abbrev

inferensi

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Social Sciences

Description

The aim of Inferensi is to publish original articles concerning statistical theories and novel applications in diverse research fields related to statistics and data science. The objective of papers should be to contribute to the understanding of the statistical methodology and/or to develop and ...