Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Inferensi
Ina Rahma
Prodi Statistika FMIPA UNM
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Social Sciences

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Penerapan Metode Hybrid Dekomposisi-Arima dalam Peramalan Jumlah Wisatawan Mancanegara Aswi Aswi; Ina Rahma; Muhammad Fahmuddin
Inferensi Vol 7, No 1 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i1.18738

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.
Co-Authors Aswi, Aswi Muhammad Fahmuddin