ANALISIS PERBANDINGAN PEMILIHAN MODA TRANSPORTASI ANGKUTAN KOTA DAN ANGKUTAN PRIBADI DI PELABUHAN TULEHU MENGGUNAKAN METODE LOGIET BINER
DOI:
https://doi.org/10.31959/js.v15i1.2654Abstract
Tulehu Port, located on Ambon Island, is the main route of the maritime transportation system for entering and exiting Ambon Island and its surrounding islands. This port plays an important role in the transportation of passengers and goods. High activity levels and long journeys to the port make many passengers choose private transportation over public transport, which is lacking in both quality and quantity. The purpose of this research is to identify the factors, percentage values of the criteria, and to determine the probability values of the selection of public transportation and private transportation modes at Tulehu Port. The choice of transportation mode plays a crucial role in transportation planning at Tulehu Port to understand the community's preferences for the chosen transportation modes. For this, a binary logit model method based on multiple linear regression analysis was used. The analysis results show that the factors of time, cost, comfort, and safety have a significant impact, with a significance value of <0.05. The mode selection variables for urban transport and private transport indicate that the time variable to Tulehu Port is 0.322, while for the mode selection from Tulehu Port, the comfort variable is 0.280. Meanwhile, the reasons respondents use urban transport to and from Tulehu Port are cost at 56% and 61%, while for private transport respondents to and from Tulehu Port, the reasons are comfort at 44% and speed at 58%. In terms of the probability of mode selection at Tulehu Port based on movement, for the route to Tulehu Port (Ambon – Tulehu), the chance of choosing urban transport is 42%, and for private transport, it is 58%. For the movement from Tulehu Port (Tulehu – Ambon), the chance of choosing urban transport is 39%, and for private transport, it is 61%.
Keyword: Binary Logiet Model; Transportation Mode Selection; Multiple Linear Regression
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Copyright (c) 2025 Sammy G.M. Amaheka, Fuad H. Ohorella, Syafruddin I. Latuconsina, Rosdiani Lestaluhu, Yusril F. I. Malik

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