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 November 5, 2024, https://igi.indrastra.com/items/show/808

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