DOI : https://doi.org/10.18517/ijaseit.10.5.12823

The Modelling of Volume and Percent Duration of Vehicle Parking for Shopping Stores in Surabaya, Indonesia

Anak Agung Gde Kartika (1), Indrasurya B Mochtar (2), Hera Widyastuti (3)
(1) Department of Civil Engineering Institute Technology Sepuluh Nopember (ITS), ITS Campus on Arif Rahman Hakim Street, Surabaya 60111, Indonesia
(2) Department of Civil Engineering Institute Technology Sepuluh Nopember (ITS), ITS Campus on Arif Rahman Hakim Street, Surabaya 60111, Indonesia
(3) Department of Civil Engineering Institute Technology Sepuluh Nopember (ITS), ITS Campus on Arif Rahman Hakim Street, Surabaya 60111, Indonesia
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How to cite (IJASEIT) :
Gde Kartika, Anak Agung, et al. “The Modelling of Volume and Percent Duration of Vehicle Parking for Shopping Stores in Surabaya, Indonesia”. International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 5, Oct. 2020, pp. 2057-6, doi:10.18517/ijaseit.10.5.12823.
Citation Format :
Both parking revenue and parking tax are the potential income for most local authorities in Indonesia since they are considered as part of their revenue. However, currently, many local authorities in Indonesia, including Surabaya, have a problem determining the target of annual parking revenue.  Meanwhile, there are growing public and private facilities in many capital cities in which many parking spaces will be provided to support their activities later. Therefore, the providing of new parking spaces will potentially contribute to the local authorities’ revenue as the consequences. The main variable to contribute to the parking revenue is the number of parked vehicles and the parking duration (progressive tariff is applied). This paper discusses parking modeling of shopping stores in Surabaya. The parking volume model is based on the following variables; accumulation, turnover, dynamic capacity, parking index, and average duration, while the model of duration is based on these following variables; accumulation, turnover, dynamic capacity, parking index, and parking volume. Since all variables has a multicollinearity problem, the model principal component regression is then used. This paper proposes the model of volume as well as percent duration of parking facility for shopping stores based on data in Surabaya.

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