IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORKS TO DETERMINE STUDENT ELIGIBILITY IN GETTING JOB

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Published Feb 28, 2023
https://doi.org/10.24252/jagti.v3i1.58
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Vol. 3 No. 1 (2023): September-Februari

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Azizah
Islamic State University Alauddin Makassar
Ayu
Islamic State University Alauddin Makassar
Azizah
Islamic State University Alauddin Makassar
Hastuti
Islamic State University Alauddin Makassar
Darmatasia
Islamic State University Alauddin Makassar

Abstract

Job recruitment selection is one of the processes carried out by agencies or companies to determine whether a person is eligible for a certain job position or not. The selection process is often carried out in a subjective manner so that it can be detrimental to companies or job applicants. In the process of determining a person's eligibility to be accepted or get a particular job, a company usually has set certain criteria. In addition, a company also often holds regular employee recruitment. This study aims to implement one of the machine learning algorithms, namely an Artificial Neural Network to build a model that can assist companies in predicting a person's eligibility for employment. The model is built with reference to certain criteria data that has been set by the company such as educational history, work experience, and capabilities. The best accuracy result of 91.18% is obtained from a model built using a learning rate parameter of 0.1 and the number of hidden layers is 10.

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Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite
[1]
A. S. Azizah Salsabila, A. A. . Zainal, A. S. Azizah Salsabila, H. Hastuti, and Darmatasia, “IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORKS TO DETERMINE STUDENT ELIGIBILITY IN GETTING JOB”, Jagti, vol. 3, no. 1, pp. 25-30, Feb. 2023.

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