DESIGN AND IMPLEMENTATION OF A DISTRIBUTED RECRUITMENT MANAGEMENT SYSTEM
ABSTRACT
Table of Content
Certiï¬cation
Acknowledgement
Abstract
List of Tables
List of Figures
CHAPTER ONE
INTRODUCTION
1.1 Background of Study
1.2 Problem Statement
1.3 Aim and Objectives of the Study
1.4 Methodology
1.5 Scope and Limitation of Study
1.6 Justiï¬cation
CHAPTER 2
LITERATURE REVIEW
2.1 Preamble
2.2 Theoretical Background of Recruitment
2.3 Information Systems
2.3.1 Types of Information Systems
2.3.1.1 Executive Information System (EIS)
2.3.1.2 Management Reporting System
2.3.1.3 Enterprise Resource Planning Systems
2.3.1.4 Business Intelligence Systems
2.3.1.5 Human Resource Management Systems
2.3.1.6 Recruitment Management Systems
2.4 What is Knowledge?
2.4.1 Measuring a Persons Knowledge
2.4.2 Knowledge Discovery in Databases
2.4.3 Data Mining
2.4.4 Data Mining and Machine Learning
2.4.4.1 Neural Networks (NN)
2.4.4.2 Case-Based Reasoning (CBR)
2.4.4.3 Genetic Algorithms (GA)
2.4.4.4 Decision Trees (DT)
2.4.4.5 Association Rules (AR)
2.4.4.6 Rough Set Theory
2.4.5 Data Mining and Statistics
2.4.5.1 Cluster Analysis
2.4.5.2 Correlation Analysis
2.4.5.3 Factor Analysis
2.4.5.4 Regression Analysis
2.4.6 Data Mining Analysis and Techniques
2.5 Data Mining in Human Resource Applications
2.5.1 Data Mining and Talent Management/Recruitment
2.6 Decision Support
2.6.1 So what is decision support?
2.6.2 Human vs. Machine Decision Making
2.6.3 Decision Support Disciplines
2.6.3.1 Operations Research (OR)
2.6.3.2 Decision Analysis Decision Analysis (DA)
2.6.3.3 Decision Support Systems (DSS)
2.6.3.4 Data Warehousing
ABSTRACT
The recruitment process has always been critical to the success or failure of organizations. Organizations constantly seek better methods of recruiting staff that will require minimal effort to seamlessly ï¬t in with the organizations business processes and thus provide recruitment agencies with the means with which to determine which universities provide the best graduates in a particular ï¬eld for recruitment.
This project work utilized a V-model software methodology, in the veriï¬cation phase requirements are gathered via observation and document analysis these requirements are then analysed using use case models data flow diagrams and entity relationship diagrams. In the Systems Design phase a software speciï¬cation document is generated and it holds technical diagrams such as, the interface design of the recruitment management system (R.M.S), its activity diagram, its architecture diagram and the logic model of the Apriori Algorithm implemented in the R.M.S. In the implementation phase various web technologies were used to implement the R.M.S, PHP was used to implement the Apriori Algorithm used to make assertions as to which higher institutions produce the best graduates in a ï¬eld of study and ï¬nally in the validation phase unit tests were carried to ensure the R.M.S is fault free.
The R.M.S developed is user friendly with interactive modules that enables organizations generate various reports and make predictions about schools that produce the best recruits in a particular ï¬eld of study. It also enables organizations schedule various exams for various candidates hence cutting out third party recruitment agencies.
Various organizations run different business processes. It is common knowledge that organizations spend a lot of resources adapting new recruits to their business processes and still get mixed results; With R.M.S organizations are guaranteed greater value for invested
resources.
The recruitment process has always been critical to the success or failure of organizations. Organizations constantly seek better methods of recruiting staff that will require minimal effort to seamlessly ï¬t in with the organizations business processes and thus provide recruitment agencies with the means with which to determine which universities provide the best graduates in a particular ï¬eld for recruitment.
This project work utilized a V-model software methodology, in the veriï¬cation phase requirements are gathered via observation and document analysis these requirements are then analysed using use case models data flow diagrams and entity relationship diagrams. In the Systems Design phase a software speciï¬cation document is generated and it holds technical diagrams such as, the interface design of the recruitment management system (R.M.S), its activity diagram, its architecture diagram and the logic model of the Apriori Algorithm implemented in the R.M.S. In the implementation phase various web technologies were used to implement the R.M.S, PHP was used to implement the Apriori Algorithm used to make assertions as to which higher institutions produce the best graduates in a ï¬eld of study and ï¬nally in the validation phase unit tests were carried to ensure the R.M.S is fault free.
The R.M.S developed is user friendly with interactive modules that enables organizations generate various reports and make predictions about schools that produce the best recruits in a particular ï¬eld of study. It also enables organizations schedule various exams for various candidates hence cutting out third party recruitment agencies.
Various organizations run different business processes. It is common knowledge that organizations spend a lot of resources adapting new recruits to their business processes and still get mixed results; With R.M.S organizations are guaranteed greater value for invested
resources.
CHAPTER 1
CHAPTER ONE
INTRODUCTION
1.1 Background of Study
Results of various research carried out over the years has shown that one of the greatest challenges facing organizations in the area of employee performance is their inability to put together techniques capable of recruiting competent employees and retaining them to achieve the goals of the organization (Gberevbie, 2008). Most of these organizations contract out the handling of staff recruitment to recruitment agencies that are subject to bias and favouritism and this more often than not results in the recruitment of incompetent staff.
According to (Banjoko 2003) employee recruitment is the act of reaching out, looking for and attracting a large number of people or a huge amount of interested candidates from which the organization can select those it considers adequate enough or most qualiï¬ed for the job. “Studies have shown that the human resource is the most valuable asset in any organization†(Adebayo et al, 2001). The human factor is one of the most important factors to be considered in the achievement of the goals of an organization. As a result, the need to put together techniques capable of recruiting competent employees and retaining them as part of an organizations workforce cannot be overemphasized.
The nature of the job market has made it almost a requirement for recruitment agencies in Nigeria to administer psychometric tests popularly called pre-employment tests or aptitude tests during the recruitment phase. Over 70% of large companies use these tests to measure how potential employees would differ in their ability to carry out tasks (Leeds University, 2010). Dragnet Solutions which is a leading Recruitment Agency in Nigeria uses a centralized computer based solution which involves inviting prospective employees to undergo these tests at speciï¬c locations and times in the country whilst ensuring the applicants never have real time access to their results.
The centralized computer based solution used by most recruitment agencies can be made more efï¬cient by employing a distributed solution using the internet to network the various computers involved in the system to facilitate the exchange of information and ensure that results are generated and can be viewed in real time whilst eliminating the need for applicants to converge at speciï¬c locations to partake in the aptitude test.
Over the years the science behind personnel recruitment has become an important area of research. Multi component systems called recruitment Management Systems have been designed to facilitate and automate the process of assessing and hiring new employees. (Recruitment management system, searchï¬nancialapplications.techtarget.com) Techniques such as Data mining and Knowledge Discovery in Databases (K.D.D) have been used over the years in some systems to ï¬nd and interpret patterns from available data with the repeated application of data mining algorithms to help make decisions about problems that rapidly change or are not speciï¬c. (Fayyad et al, 1996). The machine learning approach has also provided a step in the right direction to infer new knowledge from existing ones and this is usually expressed in the form of static data sometimes with the option of dynamic data or rules.
1.2 Problem Statement
In order to paint a clear picture of the problem to be solved a simple scenario would be used. Candidate A is a bright young graduate who just ï¬nished from the university with a ï¬rst class has completed his compulsory national youth service and is about to enter into the Nigerian labour market. He has no â€God father†or â€friends in high places†while Candidate B an average student also just graduated from the university has also completed his youth service with the difference being that In his case he knows people in all the right places. Both candidates apply for a position in a company that uses a recruitment agency to employ its members of staff candidate A performs exceedingly well in the aptitude test while candidate B performs poorly. Candidate B knowing he has performed informs his elite friends who just happen to know the C.E.O of the recruitment agency in charge.
The report that is to be sent to the hiring organization is then doctored to favour candidate B while putting candidate A at a great disadvantage thus hampering the growth of the hiring organizations. More over the data generated from the use of the system cannot be accessed easily by external organizations owing to the fact that the system is centralized and pertinent information that can be accessed by external clients is not located in a central online repository.
This bias and hoarding of information necessitates the need for a more efï¬cient means of staff recruitment hence the need to decentralize the powers of recruitment agencies with the use of a distributed decision support system which ensures that the decisions made by the system are tamper proof and not subject to the biased nature of any individual whilst ensuring that pertinent information relating to the job applicants are stored in a single repository online that can be easily accessed by other organizations who can utilise the said information to make informed decisions.
INTRODUCTION
1.1 Background of Study
Results of various research carried out over the years has shown that one of the greatest challenges facing organizations in the area of employee performance is their inability to put together techniques capable of recruiting competent employees and retaining them to achieve the goals of the organization (Gberevbie, 2008). Most of these organizations contract out the handling of staff recruitment to recruitment agencies that are subject to bias and favouritism and this more often than not results in the recruitment of incompetent staff.
According to (Banjoko 2003) employee recruitment is the act of reaching out, looking for and attracting a large number of people or a huge amount of interested candidates from which the organization can select those it considers adequate enough or most qualiï¬ed for the job. “Studies have shown that the human resource is the most valuable asset in any organization†(Adebayo et al, 2001). The human factor is one of the most important factors to be considered in the achievement of the goals of an organization. As a result, the need to put together techniques capable of recruiting competent employees and retaining them as part of an organizations workforce cannot be overemphasized.
The nature of the job market has made it almost a requirement for recruitment agencies in Nigeria to administer psychometric tests popularly called pre-employment tests or aptitude tests during the recruitment phase. Over 70% of large companies use these tests to measure how potential employees would differ in their ability to carry out tasks (Leeds University, 2010). Dragnet Solutions which is a leading Recruitment Agency in Nigeria uses a centralized computer based solution which involves inviting prospective employees to undergo these tests at speciï¬c locations and times in the country whilst ensuring the applicants never have real time access to their results.
The centralized computer based solution used by most recruitment agencies can be made more efï¬cient by employing a distributed solution using the internet to network the various computers involved in the system to facilitate the exchange of information and ensure that results are generated and can be viewed in real time whilst eliminating the need for applicants to converge at speciï¬c locations to partake in the aptitude test.
Over the years the science behind personnel recruitment has become an important area of research. Multi component systems called recruitment Management Systems have been designed to facilitate and automate the process of assessing and hiring new employees. (Recruitment management system, searchï¬nancialapplications.techtarget.com) Techniques such as Data mining and Knowledge Discovery in Databases (K.D.D) have been used over the years in some systems to ï¬nd and interpret patterns from available data with the repeated application of data mining algorithms to help make decisions about problems that rapidly change or are not speciï¬c. (Fayyad et al, 1996). The machine learning approach has also provided a step in the right direction to infer new knowledge from existing ones and this is usually expressed in the form of static data sometimes with the option of dynamic data or rules.
1.2 Problem Statement
In order to paint a clear picture of the problem to be solved a simple scenario would be used. Candidate A is a bright young graduate who just ï¬nished from the university with a ï¬rst class has completed his compulsory national youth service and is about to enter into the Nigerian labour market. He has no â€God father†or â€friends in high places†while Candidate B an average student also just graduated from the university has also completed his youth service with the difference being that In his case he knows people in all the right places. Both candidates apply for a position in a company that uses a recruitment agency to employ its members of staff candidate A performs exceedingly well in the aptitude test while candidate B performs poorly. Candidate B knowing he has performed informs his elite friends who just happen to know the C.E.O of the recruitment agency in charge.
The report that is to be sent to the hiring organization is then doctored to favour candidate B while putting candidate A at a great disadvantage thus hampering the growth of the hiring organizations. More over the data generated from the use of the system cannot be accessed easily by external organizations owing to the fact that the system is centralized and pertinent information that can be accessed by external clients is not located in a central online repository.
This bias and hoarding of information necessitates the need for a more efï¬cient means of staff recruitment hence the need to decentralize the powers of recruitment agencies with the use of a distributed decision support system which ensures that the decisions made by the system are tamper proof and not subject to the biased nature of any individual whilst ensuring that pertinent information relating to the job applicants are stored in a single repository online that can be easily accessed by other organizations who can utilise the said information to make informed decisions.
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