KLASIFIKASI EMPLOYABILITY MAHASISWA PENERIMA BEASISWA DI UNIVERSITAS TARUMANAGARA DENGAN GRAPH THEORY (MINIMUM SPANNING TREE)

Edwin Leonardo, Tri Sutrisno, Dyah Erny Herwindiati

Abstract


The application for classifying the employability of scholarship recipients with Graph Theory is a method for the classification of student employability. This method was made for Tarumanagara University which is used to replace the Tarumanagara University method which is still manual. There are 2 programming languages used to create this application, namely Visual Studio and Python. Visual Studio for the user interface and python for calculations. Testing is carried out by User Acceptance Testing (UAT) and amount testing. UAT test to check buttons and features and calculate testing to check whether the results of the manual method are the same as the K-Nearest Neighbor (K-NN) method before making it in a graph. From the two tests carried out it can be seen that the results of the mixed test data testing with an average accuracy of 92.5%, whereas for all scholarship test data with an average accuracy of 97.5%

Keywords


Student employability; K-Nearest Neighbor; Minimum Spanning Tree; Python; Visual Studio

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