DECISION SUPPORT SYSTEM OF EMPLOYEE BONUS USING THE SIMPLE ADDITIVE WEIGHTING (SAW) METHOD BASED ON THE WEBSITE (CV. Sumber Sejahtera)

Nisa, Hayatun (2022) DECISION SUPPORT SYSTEM OF EMPLOYEE BONUS USING THE SIMPLE ADDITIVE WEIGHTING (SAW) METHOD BASED ON THE WEBSITE (CV. Sumber Sejahtera). ["eprint_fieldopt_thesis_type_tugasakhir" not defined] thesis, University of Technology Yogyakarta.

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Abstract

ABSTRACT CV Sumber Sejahtera is one of the companies in Yogyakarta that handles the sale of building equipment. The equipment sold consists of bathroom doors, wheelbarrows, paralon, and also water reservoirs. This store aims to provide convenience and relief for consumers in finding goods needed by consumers in meeting the needs of building goods. Based on the results of interviews with shop owners, it is known that the process of evaluating employee performance is still subjective which is only carried out by the owner directly, so that it becomes inefficient and less effective in its assessment. In addition, the results of the assessment are inaccurate and not in accordance with the established employee performance appraisal standards. The existence of these problems causes errors in giving rewards/bonuses to employees who have the best employee performance, thus triggering a decrease in the level of performance or motivation of other employees. The purpose of this final project is to implement a decision support system in providing an assessment of employee performance at CV Sumber Sejahtera. The employee performance appraisal process is carried out using the Simple Additive Weighting (SAW) method. This is useful to facilitate decision making related to the issue of giving bonuses to employees, so that the most worthy employees will be given a monthly bonus. Keywords: Bonus, Web, Simple Additive Weighting, Decision Support System.

Item Type:	Thesis (["eprint_fieldopt_thesis_type_tugasakhir" not defined])
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User:	Kaprodi S1 Informatika UTY
Date Deposited:	23 Nov 2022 06:46
Last Modified:	23 Nov 2022 06:46
URI:	http://eprints.uty.ac.id/id/eprint/11170

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