The Weighted Product Method in the DSS for Employee rewards at the Cosmetics Warehouse
Dublin Core
Title
The Weighted Product Method in the DSS for Employee rewards at the Cosmetics Warehouse
Subject
decision support system
weighted product method
bonus
employee
cosmetic warehouse
Description
The Cosmetic Warehouse in this research is located in Purwokerto, a one-effort trade that provides beauty products. Cosmetic Warehouse Purwokerto had stood up since 2013 when Navissatul Darojah Gusmiati was founded with ten employees. The study aimed to apply the weighted product method as a decision support system for determining employee bonuses in the Purwokerto cosmetic warehouse and giving less salary and bonuses following performance employees. The Weighted Product method is a decision-making method with specific criteria. The weighted Product method is used to decide with multiplication for link attribute rating. Rating each attribute must be promoted, especially formerly with weight attribute in question; in a study, this is the data used, i.e., result data interview in the form of a later questionnaire processed by Weighted method product (WP). This research can produce results in the form of calculations with the used algorithm WP company with clear and detailed about giving employee bonuses with existing criteria. Moreover, score preference was obtained by an employee named Indri with a value equal to 0.105670687. for the score, 2nd preference was obtained by Princess with a value equal to 0.10356631, and for 3rd, obtained by Gio with a value equal to 0.101039953.
Creator
Satriani, Laela Jati
Wulandari, Hendita Ayu
Arifa, Pujana Nisya
Tahyudin, Imam
Source
Internet of Things and Artificial Intelligence Journal; Vol. 2 No. 3 (2022): Vol. 2 No. 3 (2022): Volume 2 Issue 3, 2022 [August]; 188-197
2774-4353
Publisher
Association for Scientific Computing, Electronics, and Engineering (ASCEE)
Date
2023-01-10
Rights
Copyright (c) 2022 Internet of Things and Artificial Intelligence Journal
https://ascee.org/
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Identifier
Citation
Laela Satriani Jati et al., The Weighted Product Method in the DSS for Employee rewards at the Cosmetics Warehouse, Association for Scientific Computing, Electronics, and Engineering (ASCEE), 2023, accessed December 27, 2024, https://igi.indrastra.com/items/show/808