Implementation Of The SAW Method In A Decision Support System To Determine The Best-Selling Products At Kz Allshop

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Authors: Lidia Nur Hafiza, Hari Aspriyono, Prahasti Prahasti
Cited by: 0

Abstract

The rapid development of the business world requires quick and precise decisions in determining the best-selling products to increase sales. KZ Allshop faces challenges in determining which products have the highest demand and should get more attention. For this reason, this research aims to implement the Simple Additive Weighting (SAW) method in a decision support system (SPK) to help determine the best-selling products. SAW method was chosen for its ability to give weights to various relevant criteria, such as price, quality, and number of sales. This research collects data from various products available in the store and calculates the preference value of each product based on predetermined criteria. The implementation results show that SAW method can effectively identify the best-selling products, which helps management in making more objective and data-driven decisions. Thus, the use of SAW method in this decision support system can be an effective solution in improving the efficiency of product management at KZ Allshop.

Fields of Study & Subjects

Decision Support System Applications Multi-Criteria Decision Making Data Mining and Machine Learning Applications

Publication details

Journal / source
Jurnal Media Computer Science
Volume
5
Issue
1
Pages
113–124
Publication date
21 January 2026