INTERNATIONAL JOURNAL FOR ENGINEERING APPLICATIONS AND TECHNOLOGY. Ameet.D.Shah 1, Dr.S.A.Ladhake 2.

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1 IJFEAT INTERNATIONAL JOURNAL FOR ENGINEERING APPLICATIONS AND TECHNOLOGY Multi User feedback System based on performance and Appraisal using Fuzzy logic decision support system Ameet.D.Shah 1, Dr.S.A.Ladhake 2 1 Department of Computer science and Engineering, Sipna.C.O.E.T, Maharashtra, India, 2 Principal, Department of Computer science and Engineering, Sipna.C.O.E.T, Maharashtra, India, Abstract In Multi-Source Feedback or 360 Degree Feedback, data on the performance of an individual are collected systematically from a number of stakeholders and are used for improving performance. The 360-Degree Feedback approach provides a consistent management philosophy meeting the criterion outlined previously. The 360-degree feedback appraisal process describes a human resource methodology that is frequently used for both employee appraisal and employee development. Used in employee performance appraisals, the 360-degree feedback methodology is differentiated from traditional, top-down appraisal methods in which the supervisor responsible for the appraisal provides the majority of the data. Systematic performance appraisal and ranking of candidates applying for promotion is important in strategic human resource management. The approach uses a fuzzy set theory and electronic nominal group technique for ranking decisions fairly through the multi-criteria performance appraisal process. A new ranking procedure considering the metric distance and fuzzy mean value is proposed, which makes it possible to rank order the performance of the candidates by aggregating the scores from each evaluator. A new system for performance appraisal and promotion ranking is also developed. The 360-degree feedback based appraisal is a comprehensive method where in the feedback about the employee comes from all the sources that come into contact with the employee on his/her job. The respondents for an employee can be her/his peers, managers, subordinates team members, customers, suppliers and vendors. Hence anyone who comes into contact with the employee, the 360 degree appraisal has four components that include self-appraisal, superior s appraisal, subordinate s appraisal student s appraisal and peer s appraisal.the proposed system is an attempt to implement the 360 degree feedback based appraisal system in academics especially engineering colleges. Index Terms: Multi source feedback, feedbacks, performance appraisal system, fuzzy logic based decision support system for standards/rewards. 1. Introduction In recent years multi-user feedback systems (MUFS) also known as Appraisal became very popular. When managing the human resources of an organization, appraising the performance of applicants for a particular position is central task [3].However, it is often difficult to assign an aggregate score for a candidate s performance when previous assessments were qualitative and originated from other organizations that have different performance evaluation criteria [4,5].It became popular as it has been felt for long years that one person s assessment of another individual cannot be free of biases. An operation in mobile robot is used. In this work, this approach is completed with more simulation and also theoretic results. For example, college admissions offices review applications that come from diverse schools, while corporate headquarters review applicants that come from different work environments. The difficulty is to objectively combine quantitative and qualitative evaluations of applicants to determine their acceptability to the organization, for an appraisal system to be effective, organizational members must believe that their opinions are reflected in the appraisal process [6]. Such appraisal involves a number of evaluators (or decision makers) with equal authority to assess each candidate based on both qualitative and quantitative multi- performance criteria. Performance appraisal the latest Option for career growth which is followed by many organizations across the world Get 1 http: // (C) International Journal For Engineering Applications and Technology [ ] 1

2 paid according to what you contribute this is turning the focus of organization to performance management and individual Average Percentage Performance Index performance. It AP 80 (AP) % Excellent (PI) helps to rate the 80 % > AP 60 % First Division employees and 60 % > AP 50 % Second Division 50 % > AP 40 % Third Division evaluate their AP < 40 % Fail contribution towards the organizational goals based on their performance. The appraisal results are then aggregated to rank order the performance of the candidates and select the finalists to be promoted. This is an evaluation of the performance of any individual based on the facts and often includes examples and evidences to support the information. This system has the inseparability of the bias of the evaluator as major drawback to overcome this new form of feedback 360-degree feedback is formed, it is also known as 'multiuser-rater feedback systems'. This paper introduces a methodology that uses fuzzy set theory and electronic nominal group technique for multi-criteria evaluation in the group decision making of military promotion screening. This ensures equal participation from all group members and allows managers to use analytical procedures in the final decision making. Soft computing techniques are more powerful and efficient as they provide feasible and less costly solutions compared to hard computing techniques. 1.1 The Performance Appraisal System Typically, performance appraisals have been limited to a feedback process between employees & superiors. With the increased focus on teamwork, employee development & customer service, the emphasis has shifted to employee feedback from the full circle of sources. This multi user approach to performance feedback is called assessment to connote that full circle as shown in fig. 1. Figure 1: Multi-User sources of feedback System This system is a holistic approach incorporating views from many angles, multi level & multi source appraisal. Now by changing focus from industry to academia, sources in the circle will change. Different methods are available to assess the performance. Proper questionnaire has to be designed. The steps in nominal group technique are composed of (1) generating ideas regarding the appraisal problem, (2) recording ideas from group members, (3) discussing each idea for evaluation, (4) rating and ranking the ideas, and (5) priority ordering of the alternatives based on voting and analytical methods. This technique has been successfully applied to a number of facilitating group or group decision-making problems [7 9] since it was suggested by Delbecq and Van de Ven [10]. M. and Joyce, M. [6] mentioned few other methods including management-by-objectives (MBO), work planning and review, 360 o appraisal and peer review. With all the available techniques, it is essential to understand that different organization might use different technique in assessing staff performance. However, this method requires a large number of evaluators. Also, it is not clear how to remove data points when multiple evaluators ascribe identical maximum or minimum scores. 2. Different Ways of Performance Evaluation Different scaling patterns are adopted by Academic Institutes as a Performance-Index. Average Percentage and 10 point GPA (Grade Point Average) system is the two Patterns popularly employed in majority of Institutes [12]. In first case an average percentage of score of marks are Computed and reported as a Performance Index. The scaling pattern followed could be as shown in Table-1. 2 http: // (C) International Journal For Engineering Applications and Technology [ ] 2

3 In second case of 10 point GPA system grading system followed in Universities and Colleges. The 10 point GPA is categorized as shown in table 2 1. It exists exactly one with 2. M Mðx0Þ is piecewise continuous. In this paper, trapezoidal fuzzy numbers are used. A fuzzy Number M can be defined as (a,b,c,d) as shown in Fig.1.In 3. Role of Fuzzy In Performance Evaluation The variables represent the gradual transition from high to low, true to false and are called fuzzy variables. A set containing such variables is known as Fuzzy Set. The use of linguistic terms in assessing performance has been the main Grade-Points Performance Index (PI) 10 Excellent (Ex) 9 Very Good (A) 8 Good (B) 7 Average (C) 6 Fair (D) 5 Pass (P) 4-0 Fail (F) reason for Researchers for applying the Fuzzy Techniques in the process of Student Performance Evaluation. It has been argued that one of most appropriate ways of handling multiple variables that contain imprecise data is to use Fuzzy Logic Reasoning which reflects the way of human-thinking. In this section, definitions of fuzzy set theory and linguistic variables as described by Zimmermann are reviewed (2001). This is because, in many circumstances, appraiser tends to use vaguely defined qualitative criteria in evaluating the performance of their subordinates. addition its membership function is defined as in Eq. (1). this paper are defined as follows: The basic operations of the fuzzy numbers used in Definition 1. If X is a collection of objects denoted generically by x, then a fuzzy set à in X is a set of ordered pairs: is the membership function or grade of membership of x in à that maps X to the membership space M (when M contains only the two points 0 and 1, à is non fuzzy and is identical to the characteristic function of a non fuzzy set). The range of the membership function is a subset of the nonnegative real numbers whose supremum is finite. Elements with a membership of zero degrees are normally not listed. Where Represent two trapezoidal fuzzy numbers with lower, lower modal, upper modal and upper values. Definition 2. The (crisp) set of elements that belong to the fuzzy set A at least to the degree is called the a-level set: Definition 3. A fuzzy number M is a convex normalized fuzzy set M of the real line R such that 3 http: // (C) International Journal For Engineering Applications and Technology [ ] 3

4 Definition 4. A linguistic variable is characterized by a quintuple in which x is the name of the variable; T(x) (or simple T) denotes the term set of x, i.e., the set of names of linguistic values of x, with each value being a fuzzy variable denoted generically by X and ranging over a universe of discourse U that is associated with the base variable u; G is a syntactic rule (which usually has the form of a grammar)for generation of the name,x, of values of x; and S is a semantic rule for associating with each X its meaning, which is a fuzzy subset of U. Accordingly, we propose that a set of seven terms, T, Could be given as follows: The following semantics are proposed for the set of seven terms like those in Fig. 2. The membership function of VG is let F={f1,f2,f3,...fm} be the set of basic factors in the evaluation process, and let E = {e1, e2,..., en} be a set of descriptive grades or qualitative classes used in the evaluation. evaluation model in the performance appraisal system could ease the changes need to be made in this system whenever it is necessary. The system uses fuzzy theory and electronic nominal group technique to produce fair ranking decisions through a multi-criteria performance appraisal process. The electronic nominal group technique is adopted to collect and assess the relative importance of various performance evaluation criteria collected at different organizational levels. In order to allow others to use this system, the aspect to be evaluated and the weight age for each of these aspects need to be define in the system before hand. Good engineering institutes are those where activities are designed & prompted which result in personal, social, academic & career oriented growth of students & staff. 360 degree performance appraisal is the best tool to achieve this goal. The system also has a monitoring function that uses all performance evaluation data without any removal. ACKNOWLEDGEMENT I am heartily thankful to Dr.S.A.Ladhake, Principal, Sipna College of Engineering and Technology. Whose encouragement and support resulted in the preparation of paper. I am thankful to Dept HOD for allotting us research hours. I am also thankful to all Assoc. Prof whose encouragement guidance and support from the initial to the final level. REFERENCES 1. Adnan, S. and Minwir, A. (1998), Fuzzy Logic Modeling for Performance Appraisal Systems A Framework for Empirical Evaluation, Expert Systems with Applications, Vol. 14, No. 3, p P. Allan, Avoiding common pitfalls in performance appraisal, Industrial Management (1992) Moon, C., Lee, J., Jeong, C., Lee, J., Park, S. and Lim, S. (2007), An Implementation Case for the Performance Appraisal and Promotion Ranking, in IEEE International Conference on System, Man and Cybernetics, Dessler, G. (2000), Human Resource Management (8th Edition), New Jersey, Pearson Education, Inc. 5. Terrence, H. M. and Joyce, M. (2004), Performance Appraisals, ABA Labour and Employment Law Section, Equal Employment Opportunity Committee. CONCLUSION Multifactorial evaluation model is used in assisting 6. E.W. Duggan, C.S. Thachenkary, Integrating high-level management, to appraise their employees. nominal group technique and joint application Utilizing the concept of using four multifactorial 4 http: // (C) International Journal For Engineering Applications and Technology [ ] 4

5 development for improved systems requirement determination, Information & Management 41 (2004) Jing, R.C, Cheng, C. H. and Chen, L. S. (2007), A Fuzzy-Based Military Officer Performance Appraisal System, Applied Soft Computing, Vol. 7, Issue. 3, p Tutmez, B., Kahraman, S. and Gunaydin, O. (2006), Multifactorial Fuzzy Approach to the Saw ability Classification of Building Stones, Construction and Building Materials, Vol.21, Issue 8, p G. Bortolan, R. Degani, A review of some methods for ranking fuzzy subsets, Fuzzy Sets and Systems 15 (1985) Grade point Average available Tutmez, B., Kahraman, S. and Gunaydin, O. (2006), Multifactorial Fuzzy Approach to the Saw ability Classification of Building Stones, Construction and Building Materials, Vol.21, Issue 8, p http: // (C) International Journal For Engineering Applications and Technology [ ] 5

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