Machine Learning Approach in Human Resources Department

Abdulmajeed, Ishraq; Nassreddine, Ghalia; Arid, Amal A. El; Younis, Joumana

doi:10.4018/978-1-6684-6937-8.ch013

Cited by 2 publications

(2 citation statements)

References 27 publications

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“…The final selection stage involves the participation of multiple parties in the decision-making process [17]. Based on the criteria and specifications given in the job requirements, a job analysis is conducted to achieve optimal levels of performance, contingent upon a predetermined set of parameters that prospective job candidates must fulfill [18]:…”

Section: Recruitment Processmentioning

confidence: 99%

New Recruitment Approach Based on Logistic Regression Model

Hatif Abd Almajed,

Nassreddine,

Younis

2024

Mesopotamian Journal of Computer Science

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Artificial intelligence (AI) is a pivotal technological advancement developed by humans with the aim of enhancing the quality of human existence. It signifies the capacity of a computerized machine resembling a robot to execute tasks typically performed by humans and replicate human behavior. Machine learning (ML), a subfield of AI, involves the construction of systems that acquire the ability to make predictions about new output values by leveraging existing data, without the need for human interaction. Currently, ML has been incorporated into various fields, including but not limited to medical diagnosis, image processing, prediction, classification, learning association, commerce, finance, and natural language processing. This project aims to employ ML techniques within the human resource (HR) department. The implemented model will enable the human resources department to effectively identify the most appropriate candidates for a job opening throughout the recruitment process, utilizing a comprehensive dataset and considering many criteria, all without the need for manual intervention. The construction of the model involves the utilization of an authentic dataset comprising recruitment tasks. Initially, the dataset undergoes a process of selecting the most pertinent elements from both pre-existing and extracted factors. These selected factors include educational level, age, and past experience. Furthermore, taking into consideration these aforementioned factors, a decision system is constructed utilizing the Binary classification approach. The logistic regression classifier is utilized in this investigation. Subsequently, the dataset is partitioned into two distinct subsets, namely the training subset and the testing subset. The effectiveness of the model is demonstrated by the utilization of various evaluation metrics, including the confusion matrix, recall, precision, accuracy, and F-measure values.

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Section: Recruitment Processmentioning

confidence: 99%

New Recruitment Approach Based on Logistic Regression Model

Hatif Abd Almajed,

Nassreddine,

Younis

2024

Mesopotamian Journal of Computer Science

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“…Human capital plays a pivotal role in an organization, providing an essential avenue for talent development and facilitating significant organizational growth (Abdulmajeed, Nassreddine, Amal, & Younis, 2023). In the modern era, organizations are expected to deliver exceptional efficiency and effectiveness in their operations.…”

Section: Introductionmentioning

confidence: 99%

Impact of Human Resources Management on Organizational Performance: A Case Study

C. Udokwu,

Oshioste,

Okoye

et al. 2023

Cop. Sust. Manag.

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The research was an investigation into the impact of human resources management on the performance of Nestle Plc. However, it was observed that the significant and pervasive role of human resources in the growth and development of the organization seems to have been compromised, leading to a misplacement of its role in achieving organizational performance. Inefficient management of human resource administrative processes continues to undermine the organization’s ability to effectively meet the service delivery needs of society. The primary objective of this study was to assess the influence of human resources management on the performance of Nestle Plc. To achieve this, primary data sources were utilized. The questionnaire was employed as the primary data collection tool, and regression analysis was performed to test the hypotheses. The findings of the study demonstrated that human resource development has a significant impact on employee effectiveness, operational efficiency, and the quality-of-service delivery. Based on these findings, the study recommends the implementation of regular training and development programs for employees to ensure that their knowledge is up-to-date. Furthermore, it suggests the revision of existing welfare packages to align with the current economic realities in the country.

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Machine Learning Approach in Human Resources Department

Cited by 2 publications

References 27 publications

New Recruitment Approach Based on Logistic Regression Model

New Recruitment Approach Based on Logistic Regression Model

Impact of Human Resources Management on Organizational Performance: A Case Study

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