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All Journal Journal of Information Systems Management and Digital Business
Rieuwpassa, Yonas
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Journal : Journal of Information Systems Management and Digital Business

 1 
OPTIMALISASI PENUGASAN KARYAWAN MENGGUNAKAN METODE HUNGARIAN PADA KANTOR CABANG POS AIMAS Rumetna, Matheus; Lina, Tirsa Ninia; Nahuway, Astry; Ginting, Samuel; Rieuwpassa, Yonas; Lelmaya, Yulvin; Fanindi, Aristoteles; Purba, Hebron
Journal of Information Systems Management and Digital Business Vol. 2 No. 4 (2025): Juli
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jismdb.v2i4.2535

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.
Co-Authors Fanindi, Aristoteles Ginting, Samuel Lelmaya, Yulvin Matheus Supriyanto Rumetna Nahuway, Astry Purba, Hebron Tirsa Ninia Lina