Neural Network Web-Based Human Resource Management System Model (NNWBHRMSM)

Transcription

1 Iteratioal Joural of Computer Networks ad Commuicatios Security VOL. 1, NO. 3, AUGUS 2013, Available olie at: ISSN C N C S Neural Network Web-Based Huma Resource Maagemet System Model (NNWBHRMSM) Raphael Olufemi AKINYEDE 1 ad Oladui Abosede DARAMOLA 2 12 Departmet of Computer Sciece, he Federal Uiversity of echology, P.M.B 704, Akure, Odo-State, Nigeria femi_akiyede@yahoo.com ABSRAC As busiess activities are becomig icreasig globally ad as umerous firms expad their operatios ito overseas markets, there is eed for huma resource maagemet (HRM) to esure that they hire ad keep good employees. From ages, firms/orgaizatios have bee havig great problems i gettig the right professioals ito appropriate jobs ad traiig. his research focuses at exploitig iformatio techology i order to overcome these problems. he system, which is a etwork of iter related processes, collects data from applicats through a web-based iterface ad matches with appropriate jobs. his prevets the frustratio ad some other problems iheret i the maual method of job recruitmet, which is the traditioal ustructured iterview ad kowledge based method for matchig applicats to jobs. he proposed system is a eural etwork web-based huma resource maagemet system model ruig o Iteret Iformatio (IIS) server with capabilities for Active Server Page (ASP) ad Microsoft Access; while Hypertext Markup Laguage (HML) are used for authorig web pages. Fially, the system ca ru o the miimum Petium machies with Widows XP operatig system. Keywords: Huma resource maagemet, Kowledge base (KB), Iferece egie (IE), Decisio support system (DSS), ad Neural etwork. 1 OVERVIEW OF HUMAN RESOURCE MANAGEMEN SYSEM Accordig to Ecarta (2012), it was reported that busiesses rely o effective huma resource maagemet (HRM) to esure that they hire ad keep good employees ad that they are able to respod to coflicts betwee workers ad maagemet. HRM specialists iitially determie the umber ad type of employees that a busiess will eed over its first few years of operatio. hey are the resposible for recruitig ew employees to replace those who leave ad for fillig ewly created positios. he uderstadig of huma resource maagemet is importat to ayoe who works i a orgaizatio; ad wherever people gather to work, persoel issues become importat, such issues like decisio makig cocerig recruitmet, livig, compesatio, performace evaluatio, employee disciplie, promotios ad trasfer are of great ad paramout importace. he persoel i huma resource maagemet departmet must uderstad all the rules ad regulatios guidig the employees of the firms/orgaizatios; this is very importat as it will esure that their everyday persoel actios are cosistet with those policies, to do otherwise is to ivite serious problems. As earlier oted, huma resource maagemet is cocered with the effective use of people i order to attai orgaizatioal goals ad ehace the persoal digity, satisfactio, ad well-beig of employees. But all these fuctios have bee carried out maually usig traditioal file system although few orgaizatios i Nigeria like Phillip Cosultig have goe computerized. For istace, the covetioal recruitmet exercise ivolves a process, which starts with a requisitio from the Head of each departmet of a orgaizatio who is charged with the resposibility of evaluatig,

2 76 moitorig ad cotrollig his departmetal budget. he requisitio is passed oto the persoel departmet, whose duty it is to schedule appropriate recruitmet, selectio, placemet ad traiig programs as show i Figure 1 below. Huma resources eeds Recruitmet Selectio Placemet raiig Fig. 1. Huma resources model Accordig to Akiyoku ad Uzoka (1998), persoel recruitmet s role has chaged greatly from oe that has bee based, largely, o the traditioal ustructured iterview method to oe that is recogized as highly strategic ad imperative to the overall success of the orgaizatio. It was added that, the role of the HR strategist is ow squarely focused o mechaisms to streamlie the huma resource maagemet (HRM) fuctio i order to cotribute to the overall orgaizatio s success. Computer, which has remaied oe of the most powerful tools, has served as a aid to decisio makig i recet years, mostly because of its efficiecy i terms of speed, accuracy, reliability, mass processig, cost ad security, amog others. hus, it is ot ucommo to fid computers beig applied i almost every huma activity. Presetly, a ew wave of awareess exists i people as it cocers the use of computers i admiistrative ad qualitative iformatio; it was also cofirmed that orgaizatios adopted the use of Maagemet Iformatio System (MIS) ad Decisio Support Systems (DSS) i their decisio process ad this has advaced to a web-based huma resource maagemet system o the platform of Iteret. his research outlies the beefits iheret i web-based huma resource maagemet system to streamlie processes, outsource admiistrative activities, improve efficiecies ad reduce costs. With its user friedly ad techologically advace solutio. I additio, Akiyoku ad Uzoka, (1998) also reported that (HRM) ivolves the use of both quatitative (structural) ad qualitative (ustructured) iformatio. Decisios are largely based o istitutio, priciples ad experiece. Now that the effort to build itelligece ito computig system, whereby the computer ca be used to process large volumes of quatitative ad qualitative iformatio for decisio makig is becomig reality. O the whole, HR professioals cotiue to perform may of the same activities that they did decades ago e.g. traiig, recruitig, maagig, retaiig ad payig employees. he Iteret, however, has had a sigificat impact o the way the HR professioals accomplish these tasks today, where i the past, HR activities were largely paperitesive ad highly maual, the fuctio/process today has bee trasformed ito a sophisticated computer-based process. echological improvemets have allowed HR professioals to sped less time o admiistrative tasks ad more time with employees or employee cadidates. It is therefore, ot ucommo today, to fid some orgaizatios, most especially i developed coutries, employig the use of computig system for their persoel recruitmet ad to a extet, selectio exercises. With such a system, the applicat just feed his resumes ito the computer wherever he is, by respodig to questios o the scree by typig his/her aswer, o the keyboard ad receives his employmet iformatio. Straightaway, the resumes are fed ito the orgaizatio s cetral data bak, where they ca be quickly processed. HRM is a excitig ad dyamic field, eve i this age of high iformatio techology; people are still the most importat asset to a orgaizatio. Huma resource is to support the orgaizatios missio, goals ad strategies. he orgaizatios missio is to the purpose to which it is dedicated. For example, the missio of a educatioal istitutio is to create ad dissemiate kowledge. he orgaizatios goals ad objectives state what it wats to achieve. o accomplish the orgaizatios goals ad support its strategies, huma resources objectives ad strategies must also be developed. A busiess s HRM divisio also trais or arrages for the traiig of its staff to ecourage

3 77 worker productivity, efficiecy, ad satisfactio, ad to promote the overall success of the busiess. Fially, huma resource maagers create workers compesatio plas ad beefit packages for employees. he study developed a web-based huma resource maagemet system, which will allow applicats to visit the orgaizatio employmet website before they ca eter their data. Globally, job vacacies are bee advertised by the persoel departmet ad such advertisemet have the shortcomigs which have become the factors fuelig the study of this research work, a eural etwork web-based huma resource maagemet system model (NNWBHRMSM). Such shortcomigs amog others are: i. Iability to get access to every potetial applicat due to the fact that the medium chose for the advertisemet may ot be such that is accessible to them. he result of this is that limited umber of applicats that are suitable for the jobs would oly apply. ii. Presetly i may orgaizatios, most advertisemets are oly formalities, as relatives of top maagers fill the job positios eve before the advertisemet are out. iii. Due to high cost of advertisemet, job descriptios ad specificatios are ot always well defied to the effect that potetial applicats are misiformed about the requiremets, duties ad remueratio attached with the jobs. iv. Applicats sped a lot of moey producig may copies of applicatio letters ad resumes i respose to advertisemets, which would have bee filled olie. v. May applicatios use to get lost i trasit due to poor performaces of our postal services, ad i a situatio where the selectio process is carried out, the applicats he above stated shortcomigs create a situatio whereby the orgaizatio fails to get right quality ad quatity of persoel to fill the available vacat positios. herefore, a web-based huma resource maagemet system was proposed for a effective recruitmet process that would take care of these shortcomigs of the existig system. Such system will have a data bak of employmet opportuities existig for differet orgaizatios ad a correspodig bak of potetial applicats iformatio obtaied via the web. he mai objective of the research is to develop a NNWBHRMSM, which will perform the followig: i. ehacig the productivity of the huma resource persoel (HRP), thereby improvig the productivity of the corporate orgaizatio they serve; ii. reducig time wastages i collectig, sortig ad collatig of applicatios from applicats; iii. determiig the potetial of each employee i order to esure idividual career growth ad persoal digity; Sice the system is cliet-server activities, it is built o the World Wide Web (WWW) framework. WWW provides a cost effective way of advertisig goods, services ad vacacies. he research work was carried out by a extesive review of related literature. A thorough study of the curret method of recruitig applicats was carried out, ad hece, uderstadig the iadequacies. Afterwards may recruitig orgaizatio were visited where persoal iterviews with staff were coducted. he desig of the system was doe usig Hypertext Markup Laguage (HML) for authorig web pages ad Microsoft Access Database maagemet system for the desig of the database tables. Actives server pages (ASP) ruig o iteret iformatio server was employed for the productio ad editig HML pages. CorelDraw ad Corel photo pait were employed for the productio ad editig of pictures ad images. A browser, iteret Explorer was used at the cliet side to iterpret cotets got from the web server; the browser processes the HML ad displays the web pages. he web desigs rus o Widows XP as the etwork operatig system. Real life data were used to test the system so as to esure that the desig goals were met. he rest of the paper is structured as follows:- Sectio 2 gave a overview of the related work i the area of study. I sectios 3 ad 4, we preseted the proposed system model ad framework for web-based huma resource maagemet system (WBHRMS) persoel procuremet respectively. However, sectios 5 ad 6 gave the system implemetatio ad security, while i sectio 7, we cocluded.

4 78 2 RELAED WORK Gettig the right professioals ito appropriate jobs ad traiig has bee the agitatio of every orgaizatio. For orgaizatio to do this, it must uderstad the scope ad policies ivolved. he persoel departmet advertises job vacacies ad such advertisemets are with some shortcomigs. he shortcomigs created the situatio whereby orgaizatio fails to get right professioals ito the available vacacy. Oe of the attempts to solve the shortcomigs was made i Akitola, (1995). His kowledge based applicatio for matchig applicats to job could ot be used for log because, apart from beig a Microsoft Disk Operatig System (MSDOS) based program, it was a sigle user system that could ot be used i a etworkig eviromet. o improve o what Akitola did, Uzoka, (1998) developed a kowledge based system for matchig applicats to job. Apart from the fact that the system was a MS- DOS based (sigle user) that could ot bee used i a etworkig eviromet, it was ot user friedly. Users would eed to lear lots of commads before eterig ito the system. he system also attracts high maiteace because of its relatioal structure. I additio, it caot be used i the preset world of computig because it could ot be lauched o the Iteret However, sice users are geographically distributed, we eed a better system ad the best olie huma resources maagemet system program that took care of the shortcomigs was developed by Oguwale, (2005). Oguwale, (2005) developed a web-based huma resources maagemet system, which would have helped orgaizatio i makig decisios appropriately but the system could ot hadled employmet plaig ad reports, wages ad salaries, etc. herefore, a eural etwork web-based huma resource maagemet system model which is a improvemet o the former oes was proposed. he proposed system will have a data bak of employmet opportuities existig from differet orgaizatios ad correspodig bak of potetial applicats obtaied through the Iteret. he system will help orgaizatios i gettig the right professioals ito appropriate jobs ad traiig. 3 HE MODEL We cosider group of idetical workers havig the same rage of mass. here is also a group of idetical orgaizatios havig the same type of jobs, c k etc. Orgaizatios use local formal methods such as helpwated sig posts, televisio adverts, local or atioal ewspapers. Workers who walk throughout the city, liste to V or radio adverts or read local ewspapers discover at radom the iformatio about vacacies. his implies that employed ad uemployed workers have exactly the same chace to hear about a vacacy. If the worker is uemployed, he takes the job, c k. If he is employed, we assume that he trasmits this iformatio withi his social etwork. herefore, uemployed workers ca obtai a job either idirectly through their employed frieds (who have heard about a vacat job) or directly. he system ca be mathematically model as follows: Let c 1, c 2,, c k be the jobs applicats applied for; U be the requiremets for the job ad J m be the qualificatio ad experiece of the potetial applicat s j, such that i, j, k = 1, 2, 3,..,. herefore, S j, U ad J m could be represeted as matrices as follows: S j ={S 1, S 2, S 3,., S k }, where {k =1,2,3,.,j} U ={U 1, U 2, U 3,., U t }, where {t = 1, 2, 3,.,} J m ={J 1, J 2, J 3,., J x }, where {x = 1, 2, 3,...,m} he miimum requiremets for the job c k, is a row vector U kt = [u k1 u k2 u k ] ad u k U, t = 1, 2, 3,.,; ad for each of the potetial cadidate s j that applied for the job c k, let a = 1, 2, 3,, p represet additioal requiremet from which cadidates are expected to be examied.. Also, the potetial cadidates s j s job requiremet for the job c k is a row vector j ip = [j i1 j i2 j im ] ad j im J m, p = 1, 2, 3,., m. Here, we use a model to tue the coefficiets for the fuctios f 1, f 2, f 3, f 4 for the costraits ad evaluate their relative importace. he correspodig coditioal probability of the occurrece of the job to be offered is L l P( decisio 1 w) g( w f ) ( i) a e f ( a) ( ii) a 1 e Where g represets the logistic fuctio evaluated at activatio a. Let w deote weight vector ad f the colum vector of the importace fuctios: f L f 1,..., f ]. he the decisio [ 5 is geerated accordig to the model. he weight vector w ca be adapted usig feed forward eural etwork (FFNN) topology (Schumacher, et al. 1996) ad (Bigazoli, et al. 1998). I the simplest case there is oe iput layer

5 79 ad oe output logistic layer. his is equivalet to the geeralized model with logistic fuctio. he estimated weights satisfy Eq.(iii): i w 1, 0 w 1 ( iii) i i he liear combiatio of weights with iputs f 1,...,f 4 is a mootoe fuctio of coditioal probability, as show i Eq.(i) ad Eq.(ii), so the coditioal probability of job, c k to be offered ca be moitored through the chagig of the combiatio of weights with iputs f 1, f 2, f 3, f 4. he classificatio of decisio ca be achieved through the best threshold with the largest estimated coditioal probability from group data. he class predictio of a observatio x from group y was determied by C( x) arg maxk Pr( x l k) ( iv) o fid the best threshold we used Receiver Operatig Characteristic (ROC) to provide the percetage of detectios correctly classified ad the o-detectios icorrectly classified. o do so we employed differet thresholds with rage i [0,1]. o improve the geeralizatio performace ad achieve the best classificatio, the Multilayer Perceptro with structural learig was employed (Kozma, et al. 1996) ad (Ishikawa, 1996). Such as for each c k ad each s j has applied for: v w k 2 iff sj Job Vacacy:- { c }, 1 k 4 f1 k F( f1) V ( f1), Where F is the mappig fuctio betwee persoal data ad job vacacy. ck pk, iff ck is true wk, vk iff ck wk is the total po it, where Persoal data: { s }, 1 j 4 f 2 j F( f 2 ) V ( f 2 ), Where F is the mappig fuctio betwee persoal data ad job vacacy. s p j j, iff s j is true w j, v j iff s j is the total poit w, where Academic qualificatio: { j }, 1 jm 4 j f3 m ( f 3) V ( f3), F Where F is the mappig fuctio betwee persoal data ad job vacacy. j v is p iff jm is true pm, iff jm p the total poit m m, jm m, where Job History: { u }, 1 4 f 4 F( f 4 ) V ( f 4 ), Where F is the mappig fuctio betwee persoal data ad job vacacy. u p, iff u is p, v iff u is the total poit true p, where Note that s j, c k, j m ad u are iputs; ad p, p k, p m, p =p o are poits, y, y k, y m ad y = y i are bias, v i = weighs, o i = outputs. H represet the fuctio that maps U ad J m. he we have Matches H(J m ) (U ) Let t equals total jobs applied for. If J m U ad ot ed of file (i.e. the applicat qualificatio does ot meet the job requiremet), the process s j =. Otherwise X r = M(J m ), r = 1, 2, 3..,, where M is a fuctio that returs the list of short listed applicats s t. herefore, obtai X r = M(J m ). r If ( t) p t1, select ext otherwise access the ext cadidate. he fial shortlisted is expressed as follows

6 80 1, shortlisted 0, provided f r1 X r otherwise X r p where represets the total cadidates s t that r1 are qualified for the job c k ad the f_shorlisted i represets the shortlisted cadidates ad p represet the maximum requiremet for the job k, where J m U he descriptio ad architecture of the artificial etwork are hereby give. Oe atural way the decisio makig problem ca be addressed is via the tuig the coefficiets for the soft costraits. his will largely simplify the architecture, ad it saves o both ruig time ad memory. Decisio makig ca also be viewed as a classificatio problem, for which eural etworks demostrated to be a very suitable tool. Neural etworks ca lear to make huma-like decisios, ad would aturally follow ay chages i the data set as the eviromet chages, elimiatig the task of re-tuig the coefficiets. Figure 2 above shows the architecture of the feed forward eural etwork of a web-based huma resource maagemet system (WBHRMS). he eural etwork architectures have three (3) layers. he first layer, which is the oly layer exposed to exteral sigals is called the iput layer. he layer accepts sigal (such as applicat s resume) ad trasmits it to the euros i the ext layer, which is the hidde layer. Each of these layers is liked to several other hidde layers betwee the iput ad output layers of the etwork. he layer, which may be several layers of hidde odes, performs a calculatio o the sigals reachig it ad seds a correspodig output sigal to other layers. he layer will extracts relevat features or patters (employees job specificatios) from the received sigals. he fial outputs are highly processed versio of the iput, which are the directed to the output layer -the fial layer of the etwork. Fig. 2. Artificial eural etwork model of the WBHRMS A simplified model of a euro ca easily be simulated by a artificial euro show i figure 3. he variables s j, c k, j m ad u which represet the iput lie at a particular poit i time has oe output lie each represetig the axo of the euro. Fig. 3. Fial selectio for Neural Network Model of the WBHRMS

7 81 he iput-output behaviour of the artificial euro is ow by est: f {, s, ck, jm u}, 1 3 F f ) V ( f ), ( where F is the mappig fuctio betwee persoal data ad job vacacy. s, j, u p iff s j po, v iff s, j, u is the total o,,, poit u are true p, where he variable p o is called the weight of iput lie i ad represet the syaptic trasmissio efficiecy of the syapse betwee the fial filamet of a euro ad the dedrites i of a particular euro. 4 FRAMEWORK FOR WEB-BASED HUMAN RESOURCE MANAGEMEN SYSEM (WBHRMS) PERSONNEL PROCUREMEN HE MODEL he framework proposed for web-based persoel procuremet is coceptualized i figure 5 ad 6. I this sectio, we preset the relatioal form of the huma resources maagemet coceptual objects. Statistical procedure is used for aalyzig the operatio ad implemetatio of efficiet huma resources maagemet system. he system desig is aimed at effective ad efficiet huma resources maagemet o the Iteret. he global chart of the database desig is as show i fig. 4. he major compoets of the framework are the followig, amely: kowledge base, database, iferece egie, decisio support system o he kowledge base provides specific domai kowledge (facts ad rules) about the subject acquired from the domai experts. It is desiged based o rules, which combied quatitative (structured) ad qualitative (ustructured) kowledge/iformatio ad it serves as the iformatio store for the operatioal data that are to be processed. It cotais iformatio about the prospective job applicat ad the job requiremets as are set by the establishmets employig the services of job bureau. he kowledge base of WBHRMS cotais two major iter-related databases, amely: job requiremet database, applicat database ad other databases (Ifeta, 2006). he illustrative architecture of the proposed kowledge based system for job procuremet is coceptualized i figure 3. I the database, the etire kowledge base ca be coceptualized as a etwork of relatios. A relatio is a two-dimesioal table that has a umber of rows ad colums. It is syoymous with the file cocept i the covetioal data processig eviromet. he database objects are coceptualized usig a relatioal database model. A relatio is similar to what is customarily referred to as a file ad it is geerally represeted by a set of structured tuples. Each tuple of a relatio correspods to a record i a file ad attributes correspod to fields withi a record. he geeral form of a relatio is give by R [A 1, A 2, A 3... A K, A K+1.A ], where R represets the ame of the relatio, ad the set {A i }, i = 1,2,3,, represets attributes of the relatio R (Codd, 1970). A role-based mechaism is built ito the system to specify access rights to the database system. he web-based huma resource maagemet system has six relatios i its kowledge base. he first five relatios cotai structured iformatio, while the last relatio cotais ustructured iformatio modeled i a relatio usig idicator of performace. he relatioal database supported by the system icludes: Fig. 4. Global chart of the database desig

8 82 Fig. 5. Illustrative Architecture of the Proposed Kowledge Based System i. APPLICAN-PERSONAL-DAA [applicat o, surame, other ames, dateof-birth, sex, atioality, state-of-origi, marital-status, ext-of-ki, age, address, , ii. APPLICAN- ACADEMIC/PROFESSIONAL- QUALIFICAION [applicat o, date of award, certificate, place-of-award, major subject, mior subject, class-of-award, ame, pdate of award, pstatus]. iii. APPLICAN-JOB-HISORY [applicat o, date employed, date disegaged, job code, status, employer, last-salary, coditio for leavig, ame, promotio, developmet, leaves, medical, mi year]. iv. ORGANIZAION [orgaizatio o, address, telephoe-o, lie-of-trade]. v. JOB REQUIREMEN [job code, degree, status, sex, age, atioality, years of experiece, job status of the orgaizatio]. vi. vii. JOB VACANCY [orgaizatio o, job code, job title, vacacy, ]. PERFORMANCE [applicat o, job-code, physical-test, itelligece-test, aptitudetest, score]. he iferece egie (IE) provides the reasoig ability that eables the expert system to form coclusios from specific facts ad rules about the subject provided by the kowledge base. he applicatios server would receive request/resumes from differet applicats ad seds it to them to the corporate server for heavy processig tasks. his module does the actual searchig for ad matchig of applicat s iformatio/qualificatio agaist the job request. WBHRMS adopts backward chaiig method of makig ifereces. he proposed system looks at a particular job request ad the search for the set of applicats that meet the requests ad score them accordigly. he results are later set to the qualified applicats through their addresses. he kowledge about applicat is composed of the followig: i. Persoal data. ii. iii. Academic ad professioal qualificatios. Job history, While the kowledge about the job is composed of the followig: i. Applicats registratio. ii. iii. Job ad orgaizatio requiremets. Job vacacy I each of the phases below, the ifereces draw will lead to the matchig of aother phase. See figure 6 below.

9 83 Kowledge about applicats Phase I: he system studies applicats ad jobs Applicats Phase II: Matchig of applicats to job requiremet. Academic/ Professioal qualificatios Matchig process Matchig process Matchig process Kowledge about jobs Job requiremets Job requiremets Phase III: Matchig of Academic/Professioal qualificatios with job requiremet. Figure. 6. Illustrate Architecture for the Matchig System he iferece egie (IE) provides the reasoig ability that eables the expert system to form coclusios from specific facts ad rules about the subject provided by the kowledge base with the correspodig decisio variables of the job requiremets kowledge ad report a list of applicats that are selected for some specific jobs. Decisio Support System (DSS) has two subsystems, amely cogitive ad emotioal filters. he cogitive filter carries out series of reasoig, which iclude the iductive ad deductive reasoig, o the iformatio cotets of the list of applicats appoitable for a give job produced by the iferece egie. For example, some steps could be takig i makig decisios cocerig the most suitable qualificatio ad additioal qualificatios for a particular job, age limits for the job, workig experieces i the areas related to the job, locatios of the applicats, sex whether male or female, stature, status whether married or ot married, etc. All these could form the basis for cogitive filterig of the list of selected applicats as programmed by the system egieer. he emotioal filter carries out series of reasoig, which also iclude the iductive ad deductive reasoig, o the iformatio cotext of the list of applicats appoitable for a give job produced by the iferece egie. For example, a cadidate could be preferred because of his relatioship with the people i the authority; cadidate could be disqualified because of bad behaviour, a male cadidate could be preferred to his female couterpart because of the stress that is goig to be ivolved, cadidate might be disqualified o health groud, aother oe o tribe, etc. All these could form the basis for emotioal filterig of the list of selected applicats as programmed by the system egieer. he proposed system supports a user iterface based o the iteractive web browser kow as iteret explorer ad access is gaied by supplyig userame ad password both of which aid the cotrol of access to the website. he selectio of each mai meu leads to other sub-meus, which calls o iferece procedure associated with that meu. he iferece procedure is iteractive ad it guides itelligetly to supply appropriate iformatio. O selectio of ay of the meus, alterative matchig decisios ad reasoig behid the decisios will be preseted to the expert. Fially, the system admiistrators will have the choice of applicats to match ad recommedatios will be made to huma resources departmet of the firm/orgaizatio cocered. See the figure below.

10 84 Fig. 7. Data Flow Diagram 5 HE SYSEM IMPLEMENAION he use of Iteret has moved from the old static view ad dowload of iformatio to more sophisticated dyamic use, such as e-commerce, e- govermet ad e-busiess. Ay fuctioig site cotais cliets coected to server via etwork resources. he cliets cotai the browser, which display ay iformatio dowloaded from the server. I additio, through the cliets, iformatio/data are uploaded to server for appropriate processig. I this regard, a website that could assist ay orgaizatio to receive its applicat s data via iteret is beig developed. With this website, the applicats ca search for orgaizatios with vacacies ad their addresses. Havig gotte ay appropriate firm of iterest, employmet forms are made available for them to fill ad submit, which are i tur uploaded to the orgaizatios server computers. hrough a applicatio developed i Iteret Iformatio Server, idividual firm ca the get coected to their server computers ad retrieve the applicat data for processig. Due to large flexibility of iformatio delivery over the Iteret, the system is implemeted as a stadard web-based applicatio. he applicat side requires o more tha stadard Iteret browser istalled o the local machie which the mai applicatio fuctioality is assured by the server side. he basic compoet of the system ifrastructure is preseted i Figure 8.

11 85 Fig. 8. Coceptual Diagram of the WBHRMS he diagram i figure 8 is a three-layer Iteret architecture which cosists of presetatio, cotet maagemet system ad data services. his architecture allows user to access the system through the Iteret HP protocol ad the user s request is trasformed ito a structure query laguage usig a Active Server Page commo cotet maagemet gateway, which i tur passes it to the appropriate backed system. he commo cotet maagemet gateway provides a sigle poit etry to the system via a URL. From the figure below, presetatio cosists of two mai parts. he first part is the user iterface to the system. User iterface is based o HML; so oly browser such as iteret explorer is required to use the system at the cliet (applicat) side. he secod part is the Iteret Iformatio Server (IIS) web server. he cotet maagemet system represets the iterface betwee the presetatio ad data services. At the cotet maagemet services, user s request is trasformed ito a structured query laguage where eed be usig ASP scripts. Data services represet database maagemet system, ad Microsoft Access is used to provide the required fuctioality. he system dyamically creates ad returs a HML page with the results of operatio specified by the user to the browser. Fig. 9. he System Coceptual Architecture Figure 7 ad 9 show the data flow diagram, which icludes oe static HML for home page (with forms for logi to the system), ad two CGI programs for performig autheticatio, ad database accessig defiitios. his diagram also serves as the web delivery desig diagram. 6 SECURIY he proposed system must be carefully secured from abuse ad facilities must be put i place to esure the security of the system agaist uauthorized use. I order to esure that uauthorized trasactios are ot etered

12 86 udetected the system will ot allow ay trasactio or equiry uless a user (compay user) has logged o ad etered the correct userame ad a password. Access will be deied to uauthorized users, who will be logged out after a predetermied umber of trails. Each structure or staff is assiged a uique userame ad password, which is store i the admiistratio part of the database. his prevets uauthorized access to the system. After a successful autheticatio, the mai meu of the system will be loaded. Each applicat usig the site will register ad after registratio userame ad password will be commuicated through the addressed submitted by such applicat. I additio, physical access to the computer system, diskette ad auxiliary items should be restricted to authorized staff. here are adequate programmed cotrols o the facilities for system maiteace. For example where some data are becomig obsolete ad uecessarily occupyig space o the system, provisio is bee made to remove such data. his will however oly be doe by authorized user. 7 CONCLUSION he system would be of great importace i assistig huma experts i solvig problems associated to job procuremet. It has defiitely replaced the traditioally maual compoets of backgroud ivestigatio by providig a automated data retrieval process i order to make effective ad timely decisios. he kowledge egieer uses the kowledge obtaied from huma experts to desig the system package ad draw ifereces based o some rules cocerig the static ad dyamic data cotaied i the data bak. his would eables the mai objective of the site which is to build a web-based system that will assist the huma resources departmet i procurig staff without ecessarily goig through the rigours ad problems associated with the covetioal maual method of procurig staff, to be achieved. he research developed a eural etwork webbased huma resource maagemet system model (NNWBHRMSM) that has solved the problems associated with the past researchers especially, the oe poited out i Oguwale, (2005), that is, iability to hadle employmet plaig, reports, salaries ad wages. Fially, the system NNWBHRMSM, which addresses performace, based o aptitude ad itelligece tests is a promisig oe. 8 REFERENCES [1] AKINOLA, K. G., 1995, Kowledge Based Applicatio System for Matchig Applicats to Job: B. ech. hesis. he Federal Uiversity of echology, Akure, Odo State, Nigeria. [2] AKINYOKUN, O. C ad UZOKA F.M.E, 1998, A prototype o Iformatio echology Based Huma Resource System, oc [3] AKINYOKUN, O.C, 2000, Computer: A Parter to huma experts 23rd Iaugural lecture of he Federal Uiversity of echology Akure, Nigeria. [4] BIGANZOLI, E., BORACCHI, P., MARIANI, L. ad MARUBINI, E., 1998, Feed Forward Neural Networks for the Aalysis of Cesored Survival Data: A Partial Logistic Regressio Approach, Statistics i Medicie, 17, pp [5] CODD, E., 1970, Relatioal Model for Large Shared Data Baks, Commuicatio of ACM, Vol. 13, No. 6., pp [6] ENCARA, 2012, Microsoft Corporatio. All rights reserved. [7] IFEA, U. C., 2006, Desig ad implemetatio of a web based huma resource maagemet system (WBHRMS), H.N.D Project Report, Mathematics, Statistics ad Computer Sciece Departmet, the Federal Polytechic, Ado- Ekiti, Ekiti State. [8] ISHIKAWA, M., 1996, Structural learig with forgettig, Neural Networks, Vol. 9, pp [9] KOZMA, R., SAKUMA, M., YOKOYAMA, Y. ad KIAMURA, M., 1996, O the Accuracy of Mappig by Neural Networks raied by Back porpagatio with Forgettig., Neurocomputig, Vol. 13, No. 2-4, pp [10] OGUNWALE, Y. E., 2005, Developmet of a web-based huma resource maagemet system: M. ech. hesis. he Federal Uiversity of echology, Akure, Odo State, Nigeria. [11] SCHUMACHER, M., ROSSNER, R. ad VACH, W., 1996, Neural etworks ad logistic regressio: Part I, Computatioal Statistics ad Data Aalysis, 21, pp

13 87 [12] SUAR, J. RUSEEL ad PEER NORVIG, Artificial Itelligece A moder approach, Pretice hall, Upper saddle River, New Jersey Pages 4,5 [13] UZOKA, F. M. E., 1998, Kowledge Based System for Matchig Applicats to Job: M. ech. hesis. he Federal Uiversity of echology, Akure, Odo State, Nigeria.