Agent is one of the software engineering fields with a continuous growing interest. This paper focuses on implementing an agent framework and measuring the agent in human resource management system (HRMS)domain. IAHRMS is the project name where the system

(human resource management system) will integrate with an agent and will give its users a new experience in conducting HRMS operation.The agent used breadth-first strategy in order to execute as a helper or

tutor to Human Resource people, especially in

searching for Human Resource related information, for example; information on how to use the HRMS system and information of employee working in the company.However, this project is limited to employee information only.There are few testing and metrics

have been done to ensure the system executes well in real environment

Ab Hamid, Siti Hafizah

Wong, Eric  Eu Wen

UUM Repository

  576 Implementing and Measuring Problem Solving Agent Technology of Human Resource Management System  Siti Hafizah Ab Hamida and Eric Wong Eu Wenb  Department of Software Engineering Faculty of Computer Science & Information Technology,  University of Malaya, 50630 Kuala Lumpur E-mail : asitihafizah@um.edu.my, E-mail :  bericoconut78@yahoo.com    ABSTRACT  Agent is one of the software engineering fields with a continuous growing interest. This paper focuses on implementing an agent framework and measuring the agent in human resource management system (HRMS) domain. IAHRMS is the project name where the system (human resource management system) will integrate with an agent and will give its users a new experience in conducting HRMS operation. The agent used breadth-first strategy in order to execute as a helper or tutor to Human Resource people, especially in searching for Human Resource related information, for example; information on how to use the HRMS system and information of employee working in the company. However, this project is limited to employee information only.  There are few testing and metrics have been done to ensure the system executes well in real environment.   Keywords   Human Resource Management, Agent Technology, Search Engine, Metrics  1.0 INTRODUCTION  Employee is an important asset of any organization. The organizations are becoming competitive in attracting, retaining, and recruiting good employee. To achieve the goals, human resource department uses human resource management system (HRMS) to provide immediate and comprehensive data of the employee to enable timely and accurate decision making. HRMS is an advanced and complex module which most of the users without computer background will find this system is not utilized to the utmost. Normally, main users of HRMS are human resource department’s staffs and most of them were administrative and do not have enough information technology (IT) knowledge. Lacking of IT skills will cause main users feel de-motivated to use the system. They feel aware and frustrated especially, when the system requires the users to carry out many steps to perform a task. Without these people support, any organization will lost its investment on purchasing the HRMS, will give bad impact to the HRMS usage and indirectly will decrease the company’s performance. Therefore, company needs a HRMS that has a module/function that can help support staff or staff with less computer knowledge to execute their work efficiently. To overcome this problem, the HRMS will be integrated with an agent using breadth-first strategy that will be applied in basic function of HRMS which is search information function.  2.0 OBJECTIVES  The objective of this project is to produce an agent for HRMS domain where it can get information faster and easier. The architecture of the agent module must adopt artificial intelligent (AI) knowledge, so that, the agent can use logical algorithms to resolve search-related problem when the users carry out their job. The implementation is limited to employee information module only.  3.0 REQUIREMENT ANALYSIS  This project applied scenario-based technique for requirement elicitation. Besides that, use case diagram is used to represent the requirement analysis that has been done. Use case diagram is one of scenario-based techniques for requirement elicitation; it has a description of system functionality from the users’ perspective. Figure 1 shows the use case diagram in IAHRMS.                Figure 1: Use Case Diagram     577 4.0 TECHNOLOGY USED  This project used Microsoft Visual Basic 6.0 for the IAHRMS development. Basically, Visual Basic is a Microsoft Windows programming language. Any Visual Basic program will be created in an Integrated Development Environment (IDE). The IDE allows programmer to create, run, and debug Visual Basic programs conveniently. Furthermore, the Visual Basic provides powerful features such as graphical user interfaces, event handling, access to Win32 API, object-oriented features, error handling and structured programming (Deitel & Deitel, 1999).  5.0 USER INTERFACES  The interface for agent module is for users and IAHRMS to communicate with agent. The agent module used Microsoft Agent as one-way conversational interface that will leverage all natural aspects of human social communication with animation capability, interactivity, and versatility.   To communicate with the agent, user needs to enter a question into a dialog box. Once “Submit” button is pressed, the agent system will execute the search mechanism to find solution to the problem given.  Figure 2 shows the agent system display a specific employee record. If the user wants to know details of EPF, salary and position of the employee, the user can just simply key in the input such as “EPF SALARY POSITION SHANMUGAM”, then the agent system will execute the algorithm and make query from the record of the database.  The agent system also can generate pre defined employee report. If the user requires a report of an employee, the user has to key in the employee code or employee name with the key word “CV”. The report will be generated in pre defined template and the user can print out the report via the interface. Figure 3 shows the function of agent system to generate a report.              Figure 2: Screenshot 1               Figure 3:  Screenshot 2           578             Figure 4:  Screenshot 3   Figure 4 shows the agent system provides an online help to the users of IAHRMS operation. In this case, user does not know how to edit or update an employee record. Therefore, the user has to key in a key word such as “edit” through the agent system. Once the agent system triggers an input, the agent algorithm will execute data searching mechanism to find the solution and display it to the user.   6.0 PSEUDO CODE FOR AGENT (SEARCH ENGINE)  Search engine will be responsible in finding a solution to resolve a problem. The core function of this sub system is “FindSolution”. The breadth-first search methodology will be applied in order to execute the sub system.  At the beginning, the counter controlled repetition will make comparison between keyword in arrays and input string arrays to identify the field or data that needs to be retrieved from the database. The next step is to identify whether the input sentence consists of employee information or not. Once information is defined, the program will execute a counter control loop to search record from the database. Below is the pseudo-code for the search engine.  Private Function FindSolution ()   determine which field need to retrieve from database  for n=0;n<m;n++     if ArrayDialogInput(m) = ReserveString(n) then        field = ReserveString(n)       if field = null   return null       else    call ConstructSQL (field, table, condition, type) for n=0;n<m;n++     for the remain array value, check is there an employee information     call ConstructSQL (field, table, condition, type)     execute SQL query     if record found then    employee information = ArrayDialogInput(m)        call ConstructSQL (field, table, condition, type)      while m <> 0 (m = level of breadth-first search)    find the solution with execute query    until m level for breadth-first search      wend     else   output string = request users entry more details   if solution found,    output string = solution   else    output string = no record found   call Presenter (output string, animation)  End Function  Private Function ConstructSQL (field, table, condition, type)   construct SQL statement base on type  return SQL string  End Function      Breadth-first search methodology (from for statement)   579 7.0 TESTING  7.1 Integration Testing  Integration testing takes place when all modules are integrated to create a complete system. Each module has a defined interface which is called by other program components. Figure 5 shows the overview integration of intelligent agent in IAHRMS.  The integration testing for the project involved the integration between each modules and integration with external Visual Basic components. Figure 6 shows the test result for IAHRMS integration testing.  In the testing level, test cases that are involved which are volume test, stress test and performance test will be combined together and pump ed a lot of data to do IAHRMS process. During this process, some of the system attributes like CPU usage, memory usage, SQL server response time and system response time will be captured to investigate the IAHRMS capability and performance. The result shows that the more data is processed in the system, the more CPU and memory will be used. Therefore, in order to make sure it can execute well in the future, the developer has to consider the hardware aspect of the system as well as the agent algorithm. Figure 7 shows the system testing result.                    Figure 5:  Integration Testing           Figure 6 : The result              Figure 7:  System Testing Result    010203040506070CPU/Memory Usages (%)1 10 20 50 100 200 250 500Number of DataUsage ChartCPU Usage (%)Memory Usage (%)   580 Acceptance testing is conducted to enable the developer to validate all the requirements from the user aspect. Alpha and Beta testing are used as methods of the user acceptance testing in the project. The purpose of this testing is to determine whether the IAHRMS is ready for operation and to get any error or fault that can be detected by the users only.  Table 1 illustrates the user acceptance testing result based on its usability, user experience and functionality. The users are categorized into two which are computer background users and non-computer background users. Most of users found that the intelligent agent definitely will help them to carry out their jobs faster and efficiently. However, there are 13 users found the system is bad and very bad in term of its usability. This is because they found out that the system has fix keyword in order to search information. If the user forgot the keyword, he/she will not get the information.   In term of user experience, there are 12 users from both alpha and beta groups reported it is bad and very bad. The user has to use the system many times in order to get used to it. At the beginning of using the system, the users found it takes time to use and understand the agent function. Therefore, they think it is not convenient especially for non-computer background users.  Table 1:  User Acceptance Result  Testing Criteria Measurement  Alpha Group Beta Group Total Very bad 3 2 5 Bad  5 3 8 Neutral  20 26 46 Good  17 13 30   Usability goals Very Good 5 6 11 Total  50 50 100 Very bad 4 3 7 Bad  2 3 5 Neutral  20 15 35 Good  21 27 48   User experience goals Very Good 3 2 5 Total  50 50 100 Very bad 1 2 3 Bad  9 7 16 Neutral  13 18 31 Good  22 16 38   Functionality goals Very Good 5 7 12 Total  50 50 100  8.0 SYSTEM METRICS  System metrics is used in this project because it can show the size of agent implementation in terms of its length, functionality and design structure, where the result can be used to indicate the effort and complexity of the implementation. The metrics only applies to the development of the agent only.   8.1 Length  Length is the physical size of a software product. Based on the length, the effort for the software development can be estimated. The most common measure of length is lines of code (LOC). It is difficult to calculate the length of the agent system. This is because some parts of the agent system are developed via Visual Basic. The advent of visual programming and window environment are changing dramatically the notions of the traditional software program. In Visual Basic programming environment, the programmer can easily create a window program with almost no code in the traditional sense. For example, a program with just five handwritten Visual Basic statements can easily generate an executable program of 200kb. In addition, the agent system also reuses some external build-in components in the software implementation. In this case, the actual length can not be determined; length may be predicted by considering the median expansion ratio from specification length.   It can use the size of design to predict the size of the resulting code. The design-to-code expansion ratio is,   expansion ratio a   =   size of design           size of code  At the module-design phase, length is estimated by using this formula:     m LOC = a ? Si    i=1  where Si is the size of module i (measured in term of the components of the design notation, as discussed above), m is the number of modules and a is the design-to-code expansion ration recorded. From the formula, the LOC for the agent system is estimated.            expansion ratio a    =   1518  =   2.464           616   This means the size of the design is divided by the size of code (expansion ratio) for agent system is 2.464.  number of modules m  =    18  size of the module  Si  =    80             m LOC  = a ?  S i          i=1                 18 = 2.464 ? 80 i              i=1   = 33707.52  Based on the calculation, the total line of code of the agent system is 33707.52. This number included the   581 external build in component from Microsoft and Visual Basic. One of the reasons to calculate the line of code for the agent system is to calculate the effort that contributed for development. In addition, with the line of code, it also can measure the project size as overall. Therefore, it can be concluded that the size of the agent system can be considered as medium size project. That is the reason, why the performance of the system (result from integration testing) is decreased when many data is used at one time.  8.2 Functionality  Function points are used to measure the amount of functionality in a system as described by a specification. To calculate the number of function points, FP, the unadjusted function point UFC and technical complexity factor TCF must be determined. Figure 8 shows the basic function point components from project specification.     A = external inputs = 2 B = external output = 2 C = inquiries = 2 D = external files = 2 E = internal files = 1  Figure 8:  Computing Basic Function Point Components from Specification   Table 2:  Function point Complexity Weights (Norman & Lawrence, 1997)  Weighting factor  Item Simple  Average Complex External inputs 3 4 6 External outputs 4 5 7 External inquiries 3 4 6 External files 7 10 15 Internal files 5 7 10  By considering the project specification in Figure 8 and the complexity is average, the unadjusted function count, UFC is,   UFC  = 4A + 5B + 4C + 10D + 10E   = 4(2) + 5(2) + 4(2) + 10(2) + 10(1)   = 56  Table 3:  Components of the Technical Complexity Factor (Norman & Lawrence, 1997)  Components of the technical complexity factor F1    Reliable back-up and recovery F2  Data communications F3    Distributed functions F4  Performance  F5    Heavily used configuration F6  Online data entry F7    Operational ease F8  Online update F9    Complex interface F10 Complex processing F11  Reusability F12 Installation ease F13  Multiple sites F14 Facilitate change   Technical complexity factor involves 14 contributing factors as listed in Table 3. Each component in the table is rated from 0 to 5, where 0 means the sub-factor is irrelevant, 3 means it is average and 5 means it is essential to the system being build (Norman & Lawrence, 1997).   Based on the overall consideration on the agent system, F3, F5, F9, F11, F12, and F13 are 0, that F1, F2, F6,   582 F7, F8, and F14 are 3, and that F4 and F10 are 5. Thus, the TFC calculation is,   TFC = 0.65 + 0.01(18 + 10)   = 0.93  Since UFC is 56, then the function points, FP is,   FP = UFC x TFC   = 56 x 0.93   = 52.08  The main reason to calculate function point is to present the complexity of the agent system. Based on the function point value 52.08, the complexity of agent system can consider as medium complex system.  8.3 Structure   For a program with flow graph F, the cyclomatic number is calculated as V( F) = e – n +2 where F has e arcs and n nodes. The cyclomatic numb er actually measures the number of linearly independent paths through F. This measure is objective and useful when counting linearly independent paths, but it is not at all clear that it paints a complete or accurate picture of program complexity (Norman & Lawrence, 1997).     A:  Trigger input H:  Check is record found B:  Check space I:  Construct output string C:  Split input string J:  Display output string D:  Store character into array K:  Construct SQL base on input array E:  Check is end of string L:  Query database and create dataset F:  Select common answer M:  Compare dataset G:  Compare dataset N:  Check is record found  Figure 9 : Flow Graph for Agent System   Based on Figure 9, the cyclomatic number V(F)  for the agent system as follow.    V(F) = 18 – 14 + 2           = 6  The cyclomatic number is 6, this means the module size needs to be optimal in order it to become more efficient. In addition, it can be concluded that the cost of the agent system is expensive and software developer should be productive enough to develop the system.  9.0 CONCLUSION  In conclusion, it can be said that the project has been successfully implemented and measured by considering variety of aspects of human resource management system. The system has strengths in term of flexibility architecture, interactive agent, portability, solution provision, and error prevention. However, the   577 agent could be enhanced in the future in term of its interactivity, extending usage, and interface. Therefore, human resource department will have a better solution/tool in giving a good service to its customer.  REFERENCES Deitel & Deitel (1999). Microsoft Visual Basic 6.0. New York. USA. Prentice Hall. Sommerville, I.  (2004). Software Engineering. New York, USA. Addison Wesley. Norman E. F. & Lawrence, S. (1997). Software Metrics, Second Edition. PWS Publisher.  578  

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