Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal JBMP (Jurnal Bisnis, Manajemen dan Perbankan)
Novia, Asradiani
Unknown Affiliation
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Forecasting Employee Potential through Probationary Assessment Novia, Asradiani; Yuadi, Imam
JBMP (Jurnal Bisnis, Manajemen dan Perbankan) Vol 9 No 2 (2023): September
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/jbmp.v9i2.1718

Abstract

Effective corporate governance necessitates the continual nurturing and cultivation of employee potential for long-term professional success. However, assessing an employee's potential and performance objectively and consistently from the start of their career presents a substantial difficulty in reducing any mismatches with the company's goals and expectations. This study introduces a predictive methodology that uses probationary employee performance to map their potential. The study focuses on Performance (Y-axis) and Potential (X-axis) variables using data from 265 employees at Company X who went through a probationary period. Various machine learning models, including Logistic Regression, Naive Bayes, k-NN, SVM, and Decision Tree, were used to analyze data using Orange Data Mining software. The Logistic Regression model has the highest accuracy, at 90% (0.906). Validity testing, using the Confusion Matrix, allowed individuals to be classified into nine potential groups, in accordance with the 9-Box Matrix Talent Management paradigm. This classification provides HR with a strategic tool for tailoring career development strategies based on expected potential within their respective sectors.
Co-Authors Yuadi, Imam