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dc.contributor.advisorSyahputra, Muhammad Romi
dc.contributor.authorAnjani, Laras
dc.date.accessioned2025-01-24T03:33:50Z
dc.date.available2025-01-24T03:33:50Z
dc.date.issued2024
dc.identifier.urihttps://repositori.usu.ac.id/handle/123456789/100574
dc.description.abstractPart of linear programming that is often encountered in everyday life is the assignment problem. The assignment problem involves m workers who must be assigned to n jobs, each of which has different competencies in completing the work. One method to solve this problem is the Hungarian Method. This research aims to optimize employee assignments and optimize company profits. In optimizing employee assignments, it is seen from the minimum time for completing work using the Hungarian method, while in optimizing company profits it is seen based on market demand and production costs. From the results of research using the Hungarian Method, it was found to be effective with a time of 375 minutes and 29 minutes more efficient compared to the previous time of 404 minutes. Meanwhile, for company profits after using the Hungarian Method, it is known that the optimal sales amount for MSME Bunda Dimsum before Eid 2024 is 1573 boxes of dimsum with a profit of IDR 14,541,000. That way, Bunda Dimsum MSMEs can achieve maximum sales targets in the following years.en_US
dc.language.isoiden_US
dc.publisherUniversitas Sumatera Utaraen_US
dc.subjectAssignment Problemsen_US
dc.subjectDimsum Productionen_US
dc.subjectHungarian Methoden_US
dc.subjectResearch Operationsen_US
dc.subjectProduction Costsen_US
dc.titlePenerapan Model Assignment dengan Metode Hungarian pada Optimalisasi Penugasan Karyawanen_US
dc.title.alternativeImplementation of an Asiignment Model Using the Hungarian Method to Optimize Employee Assignmentsen_US
dc.typeThesisen_US
dc.identifier.nimNIM170803013
dc.identifier.nidnNIDN0115118903
dc.identifier.kodeprodiKODEPRODI44201#Matematika
dc.description.pages54 Pagesen_US
dc.description.typeSkripsi Sarjanaen_US
dc.subject.sdgsSDGs 12. Responsible Consumption And Productionen_US


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