Modelling of key performance indicators for staff advancement in higher institutions of learning using fuzzy logic technique

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Kampala International University, School of Computing and Information Technology (SCIT)
Performance appraisal is a formal management system that provide for the evaluation of the qualities o1 an individual’s performance in an organization. One of the viable means of motivating staff in higher institutions of learning is to ensure that staff are rewarded with promotion and other benefits as at when due in practice, this is not automatic as staff advancement is usually based on a number of criteria or indicators that should be aggregated to achieve a fair and transparent judgment. However, the judgment is subjective and not transparent in many higher institutions of learning. The objective of this study, therefore, is to model some key performance indices required to achieve staff advancement in a typical higher institution of learning using a transparent approach. The concept of fuzzy logic techniques being a knowledge representation approach is used in this study, and in the process, the required attributes are identified, transformed and modeled. Specifically, the method follows the following procedures: fuzzifications, application of the fuzzy operators, rule generation, aggregation of the rule output and defuzzification. The implementation is carried out in Matlab software environment and in the process a number of rules were generated, The study shows a standard way of representing staffs achievements to pave way for advancement by following procedures that is free of subjectivity, This study further illustrates graphically the surface view of the relationship that exists among the indicators and the output (decisions); the surface view unveils a resulting output that is directly proportional. By using an interactive interface, it is recommended that the rules generated and other models represented in this study should be developed to a system using any suitable high level language. As an extension of this work, the model developed can achieve a learning capability if the technique of neural network is introduced to the fuzzy logic technique used.
A Thesis Submitted To The School Of Computing And Information Technology Kampala International University In Partial Fulfillment Of The Requirements For The Award Of Master Of Science in Computer Science (MCS) Kampala International University
Modelling, Key performance indicators, Staff advancement, Higher institutions, Learning, Fuzzy logic technique