Operational efficiency of loading and unloading activities using the time and motion study method at Tanjung Priok Port
Politeknik Pelayaran Banten
Politeknik Ilmu Pelayaran Makassar
DOI:
https://doi.org/10.62391/ejmi.v8i1.231This study aims to analyze the operational efficiency of container loading and unloading activities at Tanjung Priok Port using the Time and Motion Study method. The research was conducted to identify non-productive work activities, measure actual working times, and determine the standard time required for the loading and unloading processes. Employing a quantitative descriptive approach, data were collected through direct observation, work-time recording, documentation, and in-depth interviews with field operators. The collected data were subsequently analyzed by measuring cycle time, normal time, and standard time to assess the current level of operational efficiency. The findings reveal the persistence of non-productive periods, which are primarily caused by equipment coordination delays and operational vehicle queues. Based on the Time and Motion Study evaluation, specific bottlenecks were identified, providing actionable insights to improve work efficiency and reduce processing times. Ultimately, this study provides strategic recommendations for port management to sustainably enhance productivity, work effectiveness, and overall operational service quality.
Penelitian ini bertujuan untuk menganalisis efisiensi operasional kegiatan bongkar muat peti kemas di Pelabuhan Tanjung Priok menggunakan metode Time and Motion Study. Penelitian ini dilakukan untuk mengidentifikasi aktivitas kerja non-produktif, mengukur waktu kerja aktual, dan menentukan standar waktu baku dalam proses bongkar muat. Menggunakan pendekatan deskriptif kuantitatif, pengumpulan data dilakukan melalui observasi langsung, pencatatan waktu kerja, dokumentasi, dan wawancara dengan operator lapangan. Data yang terkumpul kemudian dianalisis melalui pengukuran waktu siklus, waktu normal, dan waktu baku untuk menilai tingkat efisiensi operasional saat ini. Hasil penelitian menunjukkan bahwa masih terdapat waktu non-produktif yang utamanya disebabkan oleh keterlambatan koordinasi alat berat dan antrean kendaraan operasional. Melalui evaluasi berbasis Time and Motion Study, penelitian ini mengidentifikasi hambatan spesifik sehingga memberikan peluang untuk meningkatkan efisiensi kerja dan mereduksi waktu proses bongkar muat. Pada akhirnya, penelitian ini diharapkan dapat memberikan rekomendasi strategis bagi manajemen pelabuhan dalam upaya meningkatkan produktivitas, efektivitas kerja, dan kualitas layanan operasional pelabuhan secara berkelanjutan.
Keywords: Operational Efficiency Loading and Unloading Time and Motion Study Port Productivity Standard Time
C. Magazzino, A. Adewale, and N. Schneider, “The trilemma of innovation , logistics performance , and environmental quality in 25 topmost logistics countries : A quantile regression evidence,” J. Clean. Prod., vol. 322, no. September, p. 129050, 2021, doi: 10.1016/j.jclepro.2021.129050.
A. Arabmaldar, A. Hatami-marbini, D. Loske, M. Hammerschmidt, and M. Klumpp, “Robust data envelopment analysis with variable budgeted uncertainty,” Eur. J. Oper. Res., vol. 315, no. 2, pp. 626–641, 2024, doi: 10.1016/j.ejor.2023.11.043.
G. Alessandria, S. Yar, A. Khederlarian, C. Mix, and K. J. Ruhl, “The aggregate effects of global and local supply chain disruptions : 2020 – 2022,” J. Int. Econ., vol. 146, p. 103788, 2023, doi: 10.1016/j.jinteco.2023.103788.
A. Hoveidafard, S. Fard, B. Golchin, and A. Ghaffari, “Identification of required stations for autonomous vehicles using AHP and TOPSIS method with GIS approach,” Sustain. Futur., vol. 10, no. June, p. 100755, 2025, doi: 10.1016/j.sftr.2025.100755.
U. Daraz, “Infrastructure , knowledge and climate resilience technologies enhancing food security : Evidence from Northern Pakistan ˇ,” vol. 10, no. June, 2025, doi: 10.1016/j.sftr.2025.100769.
A. Herbon and I. David, “Optimal manufacturer ’ s cost sharing ratio , shipping policy and production rate – A two-echelon supply chain,” Oper. Res. Perspect., vol. 10, no. July 2022, p. 100264, 2023, doi: 10.1016/j.orp.2022.100264.
S. Reyes, L. Lemire, Y. Durocher, R. Voyer, O. Henry, and P. Lan, “Investigating the metabolic load of monoclonal antibody production conveyed to an inducible CHO cell line using a transfer-rate online monitoring system,” J. Biotechnol., vol. 399, no. October 2024, pp. 47–62, 2025, doi: 10.1016/j.jbiotec.2025.01.008.
R. Aguilar-elena and J. J. Agún-gonzález, “Chi-square automatic interaction detection ( CHAID ) analysis of the use of safety goggles and face masks as personal protective equipment ( PPE ) to protect against occupational biohazards,” J. Biosaf. Biosecurity, vol. 6, no. 2, pp. 125–133, 2024, doi: 10.1016/j.jobb.2024.05.001.
T. D. Suryananda and R. Yudhawati, “Association of serum KL-6 levels on COVID-19 severity : A cross-sectional study design with purposive sampling,” Ann. Med. Surg., vol. 69, no. 6, p. 102673, 2021, doi: 10.1016/j.amsu.2021.102673.
I. Beerepoot, T. Šinik, and H. A. Reijers, “Data & Knowledge Engineering Capturing and Analysing Employee Behaviour : An Honest Day ’ s Work Record,” Data Knowl. Eng., vol. 154, no. August, p. 102350, 2024, doi: 10.1016/j.datak.2024.102350.
Ø. Per, J. Park, J. Kim, and J. Short, “Human factors validation of complex human-technology systems – Need for updating the technical basis and improving the guides and standards,” vol. 181, no. October 2024, 2025, doi: 10.1016/j.ssci.2024.106697.
J. Chen, B. Liu, and L. Yan, “Results in Physics Transport of thermal energy in epoxy matrix composites reinforced with a hybrid carbon nano fi ller,” Results Phys., vol. 14, no. May, p. 102363, 2019, doi: 10.1016/j.rinp.2019.102363.
S. Kim, W. Sohn, D. Lim, and J. Lee, “A multi-stage data mining approach for liquid bulk cargo volume analysis based on bill of lading data,” Expert Syst. Appl., vol. 183, no. August 2020, p. 115304, 2021, doi: 10.1016/j.eswa.2021.115304.
E. Bergeron, J. Audy, and P. Forget, “ScienceDirect Analysis of a methodology for simulating a port logistics system to evaluate rail capacity in bulk ports,” Transp. Res. Procedia, vol. 82, no. July 2023, pp. 3690–3709, 2025, doi: 10.1016/j.trpro.2024.12.021.
C. Dall et al., “International Journal of Nursing Studies How long do nursing staff take to measure and record patients ’ vital signs observations in hospital ? A time-and-motion study,” Int. J. Nurs. Stud., vol. 118, p. 103921, 2021, doi: 10.1016/j.ijnurstu.2021.103921.
E. Vezzali and F. Bolelli, “Engineering Applications of Artificial Intelligence State-of-the-art review and benchmarking of barcode localization methods,” Eng. Appl. Artif. Intell., vol. 147, no. December 2024, p. 110259, 2025, doi: 10.1016/j.engappai.2025.110259.
F. Bettucci, P. Lindia, P. Trunfio, and L. Sartori, “Operational state classification of agricultural Machinery using GNSS Data : A Minimal-Input approach for field efficiency assessment,” Comput. Electron. Agric., vol. 240, no. August 2025, p. 111193, 2026, doi: 10.1016/j.compag.2025.111193.
