IMPLEMENTASI DATA MINING UNTUK KLASIFIKASI DATA KANDIDAT OUTSOURCING MENGGUNAKAN METODE DECISION TREE C4.5

Ansyah, Ahmad Ardhy (2024) IMPLEMENTASI DATA MINING UNTUK KLASIFIKASI DATA KANDIDAT OUTSOURCING MENGGUNAKAN METODE DECISION TREE C4.5. Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

TOG Indonesia is a company engaged in the provision of professional IT labor services. In order to fulfill labor requirements, the company continues to create vacancies in order to meet the needs of its partners. Currently, the company employs conventional methods for candidate selection, which results in the identification of candidates that require a significant amount of time and produces inconsistent decisions. Furthermore, the candidate history data is not stored in a structured manner due to the lack of storage for the files. Consequently, this research will develop a model for candidate data classification. The chosen classification model is machine learning, specifically the decision tree C4.5, which automatically classifies based on candidate profiles and competencies. Once implemented, the results of this model demonstrate high accuracy and precision, particularly in validation using a holdout or percentage split with a 70:30 proportion of train and test data. This achieves the highest accuracy of 99% and precision of 90%. The candidate education variable emerges as the most influential factor in the candidate recommendation prediction process, as it serves as the root node of the classification tree. The model has been implemented on the website of the labor candidate classification application at TOG Indonesia. The application has been successfully created and can predict candidate data in accordance with the conditions set by the company's HR.

Item Type:

Thesis (Undergraduate)

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Fahrudin, Tresna Maulana	NIDN199305012022031007	tresna.maulana.ds@upnjatim.ac.id
Thesis advisor	Prasetya, Dwi Arman	NIDN198012052005011002	arman.prasetya.sada@upnjatim.ac.id

Subjects:

Q Science > QA Mathematics > QA76.6 Computer Programming

Divisions:

Faculty of Computer Science > Departemen of Data Science

Depositing User:

Ahmad Ardhy Ansyah

Date Deposited:

30 May 2024 05:40

Last Modified:

30 May 2024 05:40

URI:

https://repository.upnjatim.ac.id/id/eprint/23489