Bey Lirna, Cagiva Chaedar (2024) Prediksi Atrisi Voluntary Karyawan di PT.XYZ Pendekatan Ensemble Machine Learning Dengan Soft Voting Classifier. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
This research responds to the complexity of employee attrition challenges in PT.XYZ. The main goal is to develop a system for predicting the potential for voluntary attrition of employees by focusing on an in-depth analysis of voluntary attrition factors. The data used in the study used data that contained information about the work history of PT.XYZ employees for the period 2018 – 2023. The method applied is an ensemble soft voting classifier model, including SVM, Decision Tree, and binary logistic regression. The factors causing employee attrition were identified through Pearson correlation analysis and chi-square test, including the employee's home distance, employee salary, employee benefits, the year the employee occupied the work position, the length of time the employee worked in the company, the employee's last education, the employee's marital status, and the employee's work position. The soft voting classifier model can predict "Active" and "Attrition" employees as many as 60 data out of a total of 61 test data with an accuracy of 98%. Based on these findings, recommendations for employee retention strategies are formulated in the form of various considerations that need to be considered during the employee recruitment process, work-life balance programs, salary and benefit increases, career development plans, educational support, employee reward programs, and the development of an inclusive company culture.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HG Finance > HG1709 Data processing Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76.6 Computer Programming |
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| Divisions: | Faculty of Computer Science > Departemen of Data Science | ||||||||||||
| Depositing User: | Student Cagiva Chaedar Bey Lirna | ||||||||||||
| Date Deposited: | 30 Jul 2024 07:51 | ||||||||||||
| Last Modified: | 30 Jul 2024 07:51 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/28002 |
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