PENGHAMPIRAN ”NEO FUZZY NEURON” WACANA DALAM RANCANGAN KONSEPSUAL SISTEM PENILAIAN KARYAWAN
DOI:
https://doi.org/10.24034/j25485024.y2008.v12.i1.218Keywords:
fuzzy, neuron, concept, , system, decision, performanceAbstract
Computation and information technology progress in the last three decades gives real impact for management practice development. Currently some uncertainties in receiving information on management policy response is easier to be predicted. in terms of staff evaluation, inaccuracy of staff performance evaluation due to lack of good instrument caused low guarantee of objective evaluation result and free of un-bias evaluator.Neo Fuzzy Neuron approach is a thinking method which orient to human intellectual concept and to computation and information technology. This offer an alternative to predict staff behaviour evaluation. As a thinker concept, this approach can be ued as a base in developing a decision to support system in evaluating staff performance objectively and accurately; and has quite good operational feasibility.
References
Antognetti, Paolo dan Veljko Milutinovic, (1991). “Neural Networks: Concepts, Applications and Implementations”. Volume II. Prentice Hall. Englewood Cliffs, New Jersey.
Badiru, Adedeji B., Cheung, John Y., (2002). “Fuzzy Engineering Expert System with Neural Network Applications”. John Willey & Sons, Inc.
Erensal, Yasemin Claire, (2006). “Determining Key Capabilities in Technology Management Using F uzzy Analytic Hierarchy Proces: Case Study in Turkey”, International Journal of Information Science. 176, pp 2755-2770.
Kosko, Bart, (1992). “Neural Networks and Fuzzy Systems - a Dynamical System approach to Machine Intelligence”. Prentice-Hall International. Englewood Cliffs, New Jersey.
Kusumadewi, Sri, (2004). “Analisis Desain Sistem Fuzzy menggunakan Tool Box Matlab”. Edisi 1, cetakan pertama, Graha Ilmu, Yogyakarta.
Niasson, Egill dan Yih-Jeou Wang, (1990). “Introduction to Computation and Learning in Artificial Neural Networks”. European Journal of Operational Research 47. Elsevier Science Publishers B. V., North-Holland
Rao, VB dan Rao HV., (1993). “C++ Neural Networks and Fuzzy Logie”. Management Information Sources (MIS) Press, New York.
Uchino, E. dan Yamakawa, T., (1995). “ Neo-fuzzy-neuron based new approach to system modeling, with application to actual system “. In Proc. Sixth.Int. Conf. on Tools with Artificial Intelligent, New Orleans, USA, pages 564–570.
