OPTIMALISASI PENUGASAN KARYAWAN MENGGUNAKAN METODE HUNGARIAN PADA KANTOR CABANG POS AIMAS

Authors

  • Matheus Rumetna Universitas Victory Sorong https://orcid.org/0000-0001-9474-9765
  • Tirsa Ninia Lina Universitas Victory Sorong https://orcid.org/0000-0002-5944-8868
  • Astry Nahuway Universitas Victory Sorong
  • Samuel Ginting Universitas Victory Sorong
  • Yonas Rieuwpassa Universitas Victory Sorong
  • Yulvin Lelmaya Universitas Victory Sorong
  • Aristoteles Fanindi Universitas Victory Sorong
  • Hebron Purba Universitas Victory Sorong

DOI:

https://doi.org/10.70248/jismdb.v2i4.2535

Keywords:

Hungarian Method, Task Allocation, POM-QM Software, Operational Efficiency, Postal Services

Abstract

The advancement of communication technology has significantly influenced the operational dynamics of postal delivery services, including those at the Aimas Postal Branch Office (KCP Aimas) in Sorong Regency, Southwest Papua. One of the main challenges faced is the assignment problem in allocating employees for package delivery, particularly the imbalance between the number of workers and the volume of tasks. This study aims to optimize task allocation using the Hungarian Method, a linear programming approach specifically designed to solve assignment problems. The data collected include employee names, delivery destinations, and estimated travel times. The analysis involved constructing a mathematical model of the assignment problem and solving it using the Hungarian Method, supported by the POM-QM software. The findings show that the optimal total delivery time is 155 minutes, with an efficient distribution of tasks: Alexander is assigned to housing units 1–3 (40 minutes), I Gede to route Km. 24–26 (65 minutes), and Aristoteles to the Mariat Pantai–Tugu Merah area (50 minutes). These results indicate that the application of the Hungarian Method, supported by POM-QM software, not only accelerates the calculation process but also enhances the accuracy of workload distribution. Overall, this approach contributes significantly to operational efficiency and the improvement of employee productivity.

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Published

2025-07-08

Issue

Vol. 2 No. 4 (2025): Juli

Section

Articles