Forecasting The Number of Domestic Cruise Ship Passengers’ Departure at Indonesia’s Main Ports Using VARI-X with Calendar Variation Effects and The Occurence of Pandemic Covid-19

Khairunnisa, Adinda Rahma (2024) Forecasting The Number of Domestic Cruise Ship Passengers’ Departure at Indonesia’s Main Ports Using VARI-X with Calendar Variation Effects and The Occurence of Pandemic Covid-19. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Transportation is crucial for strengthening national unity, accelerating the economy, and fostering goodwill among nations. Indonesia's maritime location makes cruises popular and affordable, especially for major ports. The Eid mudik, a time-honored ritual, has seen a 3.06% increase in cruise passenger numbers in April 2023. However, the COVID-19 pandemic disrupted the flow of mudik activities, leading to a temporary ban on transportation facilities for mudik activities. This research uses data from Badan Pusat Statistika to forecast cruise passenger numbers in the future, considering calendar variations and the occurrence of COVID-19 Pandemic. This research is carried out in association for the authorities to anticipate overflowing passengers and support its mobilization namely on three ports: Tanjung Priok, Balikpapan, ands Makassar using Vector Autoregressive Integrated and the exogeneous variables or also known as VARI-X. The data shown a pattern that suitable with the Eid Al-Fitr, making Eid Al-Fitr an appropriate exogeneous variable. The model used as comparison is VARI-X (3,1) and VARI-X (4,1), ultimately VARI-X (4,1) is the better model with mean of in-sample MAPE 0.3242 and AICc 1240.098. The forecasting result tends to get higher around May and June 2024.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Cruise Passenger, Mudik, Covid-19, Multivariate Time Series, VARI-X
Subjects:	A General Works > AC Collections. Series. Collected works A General Works > AC Collections. Series. Collected works
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Adinda Rahma Khairunnisa
Date Deposited:	27 Aug 2024 04:49
Last Modified:	27 Aug 2024 04:49
URI:	http://repository.its.ac.id/id/eprint/114802

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