Managing talent in human resource : a Knowledge Discovery in Database (KDD) approach

2009 ◽  
Vol 6 (1) ◽  
pp. 51
Author(s):  
Hamidah Jantan ◽  
Abdul Razak Hamdan ◽  
Zulaiha Ali Othman
Keyword(s):  
Data Analysis ◽  
Knowledge Discovery ◽  
Human Resource ◽  
Talent Management ◽  
Past Experience ◽  
Analysis Approach ◽  
Development Finance ◽  
The Past ◽  
Knowledge Discovery In Database ◽  
The Right

In any organization, managing human talent is very important and need more attentions from Human Resource (HR) professionals. Nowadays, among the challenges of HR professionals is to manage an organization’s talent, especially to ensure the right person is assigned to the right job at the right time. Knowledge Discovery in Database (KDD) is a data analysis approach that is commonly used for classification and prediction; and this approach has been widely used in many fields such as manufacturing, development, finance and etc. However, this approach has not attracted people in human resource especially for talent management. For this reason, this paper presents an overview of some talent management problems that can be solved by using KDD approach. In this study, we attempt to implement one of the talent management tasks i.e. identifying potential talent by predicting their performance. The employee’s performance can be predicted based on the past experience knowledge which is discovered from existing databases. Finally, this paper proposes the suggested framework for talent management using KDD approach.

Human Talent Forecasting using Data Mining Classification Techniques

2012 ◽  
pp. 261-274
Author(s):  
Hamidah Jantan ◽  
Abdul Ali Hamdan ◽  
Zulaiha Othman
Keyword(s):  
Data Mining ◽  
Human Resource ◽  
Talent Management ◽  
Past Experience ◽  
Classification Task ◽  
Close Attention ◽  
Classification Techniques ◽  
Useful Knowledge ◽  
Using Data ◽  
The Right

Talent management is a very crucial task and demands close attention from human resource (HR) professionals. Recently, among the challenges for HR professionals is how to manage organization’s talents, particularly to ensure the right job for the right person at the right time. Some employee’s talent patterns can be identified through existing knowledge in HR databases, which data mining can be applied to handle this issue. The hidden and useful knowledge that exists in databases can be discovered through classification task and has been widely used in many fields. However, this approach has not successfully attracted people in HR especially in talent management. In this regard, the authors attempt to present an overview of talent management problems that can be solved by using this approach. This paper uses that approach for one of the talent management tasks, i.e., predicting potential talent using previous existing knowledge. Future employee’s performances can be predicted based on past experience knowledge discovered from existing databases by using classification techniques. Finally, this study proposes a framework for talent forecasting using the potential Data Mining classification techniques.

Human Talent Forecasting using Data Mining Classification Techniques

2012 ◽  
pp. 486-499
Author(s):  
Hamidah Jantan ◽  
Abdul Razak Hamdan ◽  
Zulaiha Ali Othman
Keyword(s):  
Data Mining ◽  
Human Resource ◽  
Talent Management ◽  
Past Experience ◽  
Classification Task ◽  
Close Attention ◽  
Classification Techniques ◽  
Useful Knowledge ◽  
Using Data ◽  
The Right

Talent management is a very crucial task and demands close attention from human resource (HR) professionals. Recently, among the challenges for HR professionals is how to manage organization’s talents, particularly to ensure the right job for the right person at the right time. Some employee’s talent patterns can be identified through existing knowledge in HR databases, which data mining can be applied to handle this issue. The hidden and useful knowledge that exists in databases can be discovered through classification task and has been widely used in many fields. However, this approach has not successfully attracted people in HR especially in talent management. In this regard, the authors attempt to present an overview of talent management problems that can be solved by using this approach. This paper uses that approach for one of the talent management tasks, i.e., predicting potential talent using previous existing knowledge. Future employee’s performances can be predicted based on past experience knowledge discovered from existing databases by using classification techniques. Finally, this study proposes a framework for talent forecasting using the potential Data Mining classification techniques.

Human Talent Forecasting using Data Mining Classification Techniques

2010 ◽  
Vol 1 (4) ◽  
pp. 29-41 ◽  
Author(s):  
Hamidah Razak Jantan ◽  
Abdul Ali Hamdan ◽  
Zulaiha Othman
Keyword(s):  
Data Mining ◽  
Human Resource ◽  
Talent Management ◽  
Past Experience ◽  
Classification Task ◽  
Close Attention ◽  
Classification Techniques ◽  
Useful Knowledge ◽  
Using Data ◽  
The Right

Talent management is a very crucial task and demands close attention from human resource (HR) professionals. Recently, among the challenges for HR professionals is how to manage organization’s talents, particularly to ensure the right job for the right person at the right time. Some employee’s talent patterns can be identified through existing knowledge in HR databases, which data mining can be applied to handle this issue. The hidden and useful knowledge that exists in databases can be discovered through classification task and has been widely used in many fields. However, this approach has not successfully attracted people in HR especially in talent management. In this regard, the authors attempt to present an overview of talent management problems that can be solved by using this approach. This paper uses that approach for one of the talent management tasks, i.e., predicting potential talent using previous existing knowledge. Future employee’s performances can be predicted based on past experience knowledge discovered from existing databases by using classification techniques. Finally, this study proposes a framework for talent forecasting using the potential Data Mining classification techniques.

scholarly journals Challenges and priorities in talent management during the global pandemic caused by COVID-19

2021 ◽  
Vol 5 (2) ◽  
pp. 94-103
Author(s):  
Luba Tomcikova ◽  
Nella Svetozarovova ◽  
Jana Coculova
Keyword(s):  
Human Resources ◽  
Human Resource ◽  
Slovak Republic ◽  
Selection Process ◽  
Talent Management ◽  
The Past ◽  
Significant Relationships ◽  
Global Pandemic ◽  
Human Resources Managers ◽  
Recruitment And Selection

The paper deals with the talent management issue as one of the effective human resource management practices during the global pandemic caused by COVID-19 and points to the main challenges and priorities in the research area. Talent management has undergone a dynamic development in recent years. It has recently become a frequently discussed concept among business and academics alike and one of the priorities of the modern management of all companies. The paper also presents the results of research carried out on a sample of 137 human resources managers. Respondents who participated in the questionnaire survey are human resources managers in companies operating in the Slovak Republic at national and international markets. Data were collected using the online questionnaire. For the research, two research hypotheses were established. The hypotheses aimed to determine whether there are statistically significant relationships between the scale of talent recruitment and selection process over the past year; the change in the management and organizational style of the company during the COVID-19 pandemic; the existence of the statistically significant relationship between the budget allocated to talent management and headhunting practices over the last year. The hypotheses were verified using correlation analysis and the methods of inductive statistics. Testing the statistically significant relationships verified hypothesis H1. It confirmed the existence of statistically significant relationships between the scale of the talent recruitment and selection process over the past year and the change in management and organization of the company during the COVID-19 pandemic. The hypothesis H2 was rejected. It stated the absence of statistically significant relationships between the budget for talent management in the organization during the COVID-19 pandemic and the competition for qualified talent for the last year. The questionnaire survey results pointed how human resources managers in companies operating in the Slovak Republic perceive the situation associated with the current COVID-19 pandemic. The findings identified the pandemic impact on talent management and how human resources managers see human resource management's future and priorities.

scholarly journals Investigating relationship of talent management and organizational entrepreneurship

2019 ◽  
Vol 2 (1) ◽  
pp. 25-37 ◽  
Author(s):  
Fereydoon Azma ◽  
Mohammad T. Farahbakhsh ◽  
Reza Safarzad ◽  
Ehsan Farahnaki
Keyword(s):  
Human Resource ◽  
Selection Criteria ◽  
Talent Management ◽  
Comprehensive Strategy ◽  
Top Managers ◽  
Golestan Province ◽  
Spss Software ◽  
The Right ◽  
Relationship Of ◽  
The Relationship

Introduction: talent management is a comprehensive strategy and an approach to international human resource practices and a commitment to widespread sharing of the belief that human resource is a priority and a source of competitive advantage. Talent management ensures the organizations that competent individuals with the right skills have taken the right position. The aim of this study was to investigate the relationship between talent management and organizational entrepreneurship. Methodology: The present study is an applied one in terms of its nature and purpose, and it is a descriptive and correlational one in terms of the data collection method to test the hypothesis. The population of this study included experts, officials, supervisors and middle and top managers of Golestan province Gas Company who have at least 7 years’ experience. Accordingly, a total number of 51 participated in the study. A questionnaire was used to collect data. Data analysis was carried out through SPSS software for descriptive data and SMART PLS software for inferential data. Results: This study shows that there is a significant positive relationship between talent management and organizational entrepreneurship, and components of each of the main criteria also have a significant relationship with each other. Conclusion: The findings suggest that managers should improve their organization's talent management system in order to increase innovation and competitiveness. These systems can complete and implement various initiatives by creating opportunities to achieve talent resources and providing transparency in selection criteria.

COMMONWEALTH Forum: The Politics of Science or the Science of Politics

Commonwealth ◽  
2017 ◽  
Vol 19 (1) ◽  
Author(s):  
John Arway
Keyword(s):  
Public Policy ◽  
Natural Resource ◽  
Factual Information ◽  
The Past ◽  
Difference Of Opinion ◽  
History Of ◽  
The Right ◽  
Scientific Facts ◽  
Environmental Agency ◽  
Laws And Regulations

The challenges of including factual information in public policy and political discussions are many. The difficulties of including scientific facts in these debates can often be frustrating for scientists, politicians and policymakers alike. At times it seems that discussions involve different languages or dialects such that it becomes a challenge to even understand one another’s position. Oftentimes difference of opinion leads to laws and regulations that are tilted to the left or the right. The collaborative balancing to insure public and natural resource interests are protected ends up being accomplished through extensive litigation in the courts. In this article, the author discusses the history of environmental balancing during the past three decades from the perspective of a field biologist who has used the strength of our policies, laws and regulations to fight for the protection of our Commonwealth’s aquatic resources. For the past 7 years, the author has taken over the reins of “the most powerful environmental agency in Pennsylvania” and charted a course using science to properly represent natural resource interests in public policy and political deliberations.

Rancangan Sistem Pengukuran Kinerja Berbasis Human Resource Scorecard Pada Universitas Muhammadiyah Luwuk

2020 ◽  
Vol 10 (1) ◽  
pp. 63-71
Author(s):  
Nurhaeda Abbas ◽  
Anggraini Sukmawati ◽  
Muhammad Syamsun
Keyword(s):  
Performance Measurement ◽  
Human Resource ◽  
Performance Measurement System ◽  
Group Discussions ◽  
Strategic Objectives ◽  
Depth Interview ◽  
And Performance ◽  
The Right ◽  
Hierarchy Process ◽  
The Relationship

Today the performance measurement of Muhammadiyah Luwuk uUniversity’s performance has not formulated yet based on University’s vision and mission. It will affect the strategic steps needed and performance improvement efforts in the future.  Human resource scorecard is the right system to be applied in Muhammadiyah Luwuk University. The purpose of this study is to designed a performance measurement system at Muhammadiyah Luwuk University using the Human Resource Scorecard with four perspectives: stakeholder, academic management and kemuhammadiyaan, operational and innovation, as well as and learning. Data was analyzed by analytical hierarchy process method. This research was conducted by distributing questionnaires, focus group discussions and in-depth interview with stakeholders at Muhammadiyah Luwuk University. The results showed that there were 14 strategic objectives and 33 key performance indicators to be achieved by the priority objectives, which are: empowerment and development of faculty, increased administrative process quality, improved sound budget performance and, improvement of the relationship with stakeholders.

Accelerating Agricultural Growth—Is Irrigation Institutional Reform Necessary? (Distinguishedl Lecture)

1996 ◽  
Vol 35 (4I) ◽  
pp. 399-417 ◽  
Author(s):  
John W. Mellor
Keyword(s):  
Growth Rates ◽  
Irrigation System ◽  
Institutional Reform ◽  
Residual Effect ◽  
Agricultural Growth ◽  
The Past ◽  
Major Reform ◽  
History Of ◽  
The Right ◽  
Economic Growth Rates

The right to the flow of income from water is vigorously pursued, protected, and fought over in any arid part of the world. Pakistan is of course no exception. Reform of irrigation institutions necessarily changes the rights to water, whether it be those of farmers, government, or government functionaries. Those perceived rights may be explicit and broadly accepted, or simply takings that are not even considered legitimate. Nevertheless they will be fought over. Pakistan has a long history of proposals for irrigation reform, little or none being implemented, except as isolated pilot projects. Thus, to propose major changes in irrigation institutions must be clearly shown to have major benefits to justify the hard battles that must be fought and the goodwill of those who might win those battles for reform. Proponents of irrigation institution reform have always argued the necessity of the reforms and the large gains to be achieved. Perhaps, however, those arguments have not been convincing. This paper will briefly outline the failed attempts at irrigation reform to provide an element of reality to the discussion. It will then proceed to make the case of the urgency of reform in a somewhat different manner to the past. Finally, current major reform proposals will be presented. This paper approaches justification of irrigation reform by focusing on the agricultural growth rate. It does so because that is the critical variable influencing poverty rates and is a significant determinant of over-all economic growth rates. The paper decomposes growth rates and suggests a residual effect of deterioration of the irrigation system that is large and calls for policy and institutional reform. The data are notional, suggesting the usefulness of the approach and paves the way for more detailed empirical analysis and enquiry for the future.

Analisis Data Pembayaran Kredit Nasabah Bank Menggunakan Metode Data Mining

2013 ◽  
Vol 4 (1) ◽  
pp. 18-27
Author(s):  
Ira Melissa ◽  
Raymond S. Oetama
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Knowledge Discovery In Database

Data mining adalah analisis atau pengamatan terhadap kumpulan data yang besar dengan tujuan untuk menemukan hubungan tak terduga dan untuk meringkas data dengan cara yang lebih mudah dimengerti dan bermanfaat bagi pemilik data. Data mining merupakan proses inti dalam Knowledge Discovery in Database (KDD). Metode data mining digunakan untuk menganalisis data pembayaran kredit peminjam pembayaran kredit. Berdasarkan pola pembayaran kredit peminjam yang dihasilkan, dapat dilihat parameter-parameter kredit yang memiliki keterkaitan dan paling berpengaruh terhadap pembayaran angsuran kredit. Kata kunci—data mining, outlier, multikolonieritas, Anova

Sign in / Sign up

Export Citation Format

Share Document