Forecasting Hotel Occupancy Rates in Bali Province using the SARIMAX Method with Tourist Data as an Exogenous Variable

Tourism is a crucial economic sector in Bali, Indonesia. Sustainable tourism management requires an understanding of the dynamics between tourist numbers and hotel occupancy levels. This study uses the SARIMAX (Seasonal Autoregressive Integrated Moving Average) method to estimate between the two indicators and reveals a positive correlation between the two indicators. The SARIMAX model effectively captures seasonal patterns and external factors, providing accurate forecasts and supporting tourism management in Bali. Monthly data from 2010 to 2023 were analyzed. Accurate estimates can help tourism stakeholders in formulating appropriate management strategies to optimize the tourism sector. Implementing the right strategy can help ensure the preservation of the local environment and culture, as well as long-term economic benefits for Bali. From the data we use the SARIMAX (6,1,0) (1,1,0)12 model with an AIC value of 1920.553 and a MAPE value of 27%.

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Journal
EKSAKTA Journal of Sciences and Data Analysis
Published
2024-10-23
DOI
https://doi.org/10.20885/eksakta.vol5.iss2.art2
Primary Topic
Community-based Tourism Development and Sustainability
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article
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article

Forecasting Hotel Occupancy Rates in Bali Province using the SARIMAX Method with Tourist Data as an Exogenous Variable

M. Al Haris, Ihsan Fathoni Amri, A. S. Arya, Yolan Triky et al.
EKSAKTA Journal of Sciences and Data Analysis
Community-based Tourism Development and Sustainability
article

Forecasting Hotel Occupancy Rates in Bali Province using the SARIMAX Method with Tourist Data as an Exogenous Variable

M. Al Haris, Ihsan Fathoni Amri, A. S. Arya, Yolan Triky, Kaia Raissa Akmalia, Abdul Ghufron
article en

Abstract

Tourism is a crucial economic sector in Bali, Indonesia. Sustainable tourism management requires an understanding of the dynamics between tourist numbers and hotel occupancy levels. This study uses the SARIMAX (Seasonal Autoregressive Integrated Moving Average) method to estimate between the two indicators and reveals a positive correlation between the two indicators. The SARIMAX model effectively captures seasonal patterns and external factors, providing accurate forecasts and supporting tourism management in Bali. Monthly data from 2010 to 2023 were analyzed. Accurate estimates can help tourism stakeholders in formulating appropriate management strategies to optimize the tourism sector. Implementing the right strategy can help ensure the preservation of the local environment and culture, as well as long-term economic benefits for Bali. From the data we use the SARIMAX (6,1,0) (1,1,0)12 model with an AIC value of 1920.553 and a MAPE value of 27%.

EKSAKTA Journal of Sciences and Data Analysis
Universitas Muhammadiyah Semarang (ID)
Openalex Percentile: Top 68%
Community-based Tourism Development and Sustainability
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