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

  • Leonardo E
  • Sutrisno T
  • Herwindiati D
N/ACitations
Citations of this article
9Readers
Mendeley users who have this article in their library.

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%

Cite

CITATION STYLE

APA

Leonardo, E., Sutrisno, T., & Herwindiati, D. E. (2020). KLASIFIKASI EMPLOYABILITY MAHASISWA PENERIMA BEASISWA DI UNIVERSITAS TARUMANAGARA DENGAN GRAPH THEORY (MINIMUM SPANNING TREE). Jurnal Ilmu Komputer Dan Sistem Informasi, 8(2), 209. https://doi.org/10.24912/jiksi.v8i2.11498

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free