DEPARTMENT SELECTION USING GAME THEORY

In Institut Teknologi Bandung (ITB), new students are not directly accepted into their departments, but will go through a preparation phase (TPB) in each faculties first for their first year. At the end of TPB, a department selection will be held to determine each student’s university major. Depa...

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Bibliographic Details
Main Author: Dustin Pingnomo, Theodore
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/83750
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:In Institut Teknologi Bandung (ITB), new students are not directly accepted into their departments, but will go through a preparation phase (TPB) in each faculties first for their first year. At the end of TPB, a department selection will be held to determine each student’s university major. Department selection can be modeled as a game using game theory, and the ideality of the selection result can be seen through this model. The players in this game are the Faculty of Mathematics and Natural Sciences (FMIPA) departments, with cooperative behavior. Each department has its own payoff function that is associated with the correlation value between students and university majors, based on the selection criteria. The ideality of the selection result can be seen through each department’s payoff value, where a selection result is said to be ideal if the sum of all departments’ payoff value is maximal. The selection game can be modeled as a weighted complete bipartite graph, with the partitions of the graph correspond with the students set and the departments set. The weight of each edge corresponds with the correlation value between the student and the department that is connected through the edge. This graph can be modified by duplicating the department nodes so that the number of node each department has is equal to the maximum quota of the department, then adding student nodes so that the number of student nodes is equal to the number of department nodes. A maximumweight perfect matching can be found on the modified graph using Hungarian algorithm. The matching that is obtained from the algorithm represents the ideal selection result.