基于模糊推理系统的天津大学讲师成绩指标测量

K. Umam, Eldy Satriya Wibawa
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引用次数: 0

摘要

作为衡量讲师绩效的一种努力,STIKOM PGRI Banyuwangi实施了讲师成就指数(LAI)的测量。规模是通过使用李克特量表收集学生对讲师九个绩效指标的绩效评分来进行的。然而,这种方法只能从指标得分中产生平均值。这种方法还不能描述讲师的表现质量。因此,需要另一种机制来了解讲师的表演质量。一种可用的方法是模糊推理系统(FIS)。该技术用于将学生给出的讲师的表现平均分数映射到三个表现质量级别,即,良好,足够和PO,或基于预定义的成员函数。然后使用预定义的规则对这些模糊值进行评估,以确定讲师的表演质量。然后从这些值的去模糊化阶段得到LAI评分。使用这种方法得到的LAI评分不同于旧的机制。它可以根据性能质量来提高分数。质量越好,讲师得到的分数越高,反之亦然。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lecturer Achievement Index Measurement Using Fuzzy Inference System at STIKOM PGRI Banyuwangi
As an effort to measure lecturer performance, STIKOM PGRI Banyuwangi implements the measurement of the Lecturer Achievement Index (LAI). The size is conducted by collecting student ratings of the lecturer's performance using a Likert scale on nine performance indicators. However, this method only produces an average value from the indicator scores. This method has not been able to describe the quality of a lecturer's performance. Therefore, another mechanism is needed so that the lecturer's performance quality can be known. One method that can be used is the Fuzzy Inference System (FIS). The technique is used to map the lecturer's performance average scores given by students into three levels of performance quality, i.e., Good, adequate, and PO, or based on predefined membership functions. These fuzzy values then evaluated using predefined rules to determine the lecturer's performance quality. The LAI score is then obtained from the defuzzification stage of these values. By using this method, the LAI score obtained is different from the old mechanism. It can enhance the score based on performance quality. The better the quality, the better the score that the lecturer gets, and vice versa.
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