Managing the Congestion for Delivering and Receiving Truck Container at the Tanjung Priok Terminal by Analyzing the Congestion at Koja Container Terminal

Abstract

This study aimed to analyze the congestion that occurred around the Koja Container Terminal to develop strategies that will aid in managing the congestion presently occurring at the Tanjung Priok Container Terminal. Dwelling time, ship delay, gate server down, equipment damage, and lack of support for the truck arrival system were some causes of congestion in the Tanjung Priok area. There was an improvement in the truck arrival system (TAS) and Chassis Exchange Terminal (CET). Analyzing the inefficiency in managing the arrival of trucks for container pickup is the strategy needed for controlling congestion. This research was conducted by observing the field movements at the Koja Container Terminal and interviewing the people who experienced congestion in the terminal. This methodology was proposed to aid in efficiently operating the Tanjung Priok Port and alleviate truck congestion. Because it provides systematic, structured, and problem-solving benefits, this study is expected to be a source of consideration for stakeholders when making decisions. The result of this study will help improve the management of congestion at Terminal Koja.


Keywords: Managing Congestion, Delivering and Receiving, Truck Container, Terminal Container, Port

References
[1] Herdian T, Kusumastanto T, Sartono B. Operational Analysis of Container Truck. Adv. Eng. Res. 2017;147:70–85.

[2] Chen G, Jiang L. Managing customer arrivals with time windows: a case of truck arrivals at a congested container terminal. Ann Oper Res. 2016;244(2):349–65.

[3] Krisnawati S, Sugandi, Bijaksana G. Upaya Peningkatan Kinerja Tenaga Kerja Bongkar Muat Di Pelabuhan Marunda Jakarta. J. Manaj. Bisnis Transp. dan Logistik. 2019;5(2):267-https://doi.org/ISSN. 2407-635X.

[4] Chen G, Govindan K, Yang Z. Managing truck arrivals with time windows to alleviate gate congestion at container terminals. Int J Prod Econ. 2013;141(1):179–88.

[5] Chen G, Govindan K, Golias MM. Reducing truck emissions at container terminals in a low carbon economy: proposal of a queueing-based bi-objective model for optimizing truck arrival pattern. Transp Res, Part E Logist Trans Rev. 2013;55(X):3– 22.

[6] Hamilton AB, Finley EP. Qualitative methods in implementation research: an introduction. Psychiatry Res. 2019 Oct;280:112516.

[7] Thelwall M, Nevill T. Is research with qualitative data more prevalent and impactful now? Interviews, case studies, focus groups and ethnographies. Libr Inf Sci Res. 2021;43(2):101094.

[8] Zeng Q, Feng Y, Yang Z. Integrated optimization of pickup sequence and container rehandling based on partial truck arrival information. Comput Ind Eng. 2019;127:366– 82.

[9] Torkjazi M, Huynh N, Shiri S. Truck appointment systems considering impact to drayage truck tours. Transp. Res. Part E Logist. Transp. Rev. 2017;116(September): 208-https://doi.org/10.1016/j.tre.2018.06.003.

[10] Zhao W, Goodchild AV. The impact of truck arrival information on container terminal rehandling. Transp Res, Part E Logist Trans Rev. 2010;46(3):327–43.

[11] Dekker R, Van Der Heide S, Van Asperen E, Ypsilantis P. A chassis exchange terminal to reduce truck congestion at container terminals. Flex Serv Manuf J. 2013;25(4):528–42.