METODE SIMPLE ADDITIVE WEIGHTING (SAW) PADA SISTEM PENDUKUNG KEPUTUSAN PENILAI KINERJA GURU (PKG) (STUDI KASUS SMP 17 1 PAGELARAN)

  • Ridhawati E
  • Sirega G
  • Iriawan D
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Abstract

ABSTRACT Decision support systems (SPK) are part of computer-based information systems including knowledge-based systems or knowledge management that are used to support decision making within an organization or company. Teachers and professional teaching staff are a must for both elementary, middle and high school in implementing the quality education process. Likewise with SMP 17 1 Pagelaran, it always encourages the improvement of teacher professionalism by monitoring the performance of teachers in implementing their duties and responsibilities, so that they can achieve specified competency standards. Making the support system decision is one way to help in determining the assessment junior high school teacher at 17 1 show expected the system could detect whichever alternative based on the upper best multiplication weights every criteria. The criteria rated in the performance of teachers are loyalty , work performance , responsibility , obedience , honesty and cooperation he model used for spk this is fuzzy multiple attribute decision making ( fmadm ) .The simple additive weighting ( saw ) was chosen because this method determine the value of weights to any attribute , then continued with a perankingan who will select alternative best of a number of alternatives , in this case the alternative referred to was teachers who has the highest petrokimia based on the criteria With the ranking method, it is expected that the assessment will be more appropriate because it is based on the criteria and weight values ​​that have been determined so that it will get more accurate results on who will receive the reward

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Ridhawati, E., Sirega, G. r K., & Iriawan, D. (2018). METODE SIMPLE ADDITIVE WEIGHTING (SAW) PADA SISTEM PENDUKUNG KEPUTUSAN PENILAI KINERJA GURU (PKG) (STUDI KASUS SMP 17 1 PAGELARAN). Jurnal Informasi Dan Komputer, 6(2), 38–49. https://doi.org/10.35959/jik.v6i2.108

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