Decision Support System for Laptop Selection Recommendations Using the Weigted Product (WP) Method

The many types of specifications, colors and brands of laptops are complicated and confusing for ordinary people who are going to buy laptops. The reason is, there are many variants of laptops on the market with different specifications. To help potential consumers in choosing a laptop that suits their needs, a decision support system (SPK) is needed that can provide the most appropriate laptop recommendations. This study discusses the decision support system for laptop selection recommendations using the Weighted Product (WP) method. This method is used to help consumers choose a laptop that suits their needs based on predetermined criteria, such as processor, RAM, Storage, and Price. After a search of the vector to get the ranking, the largest vector value of 0.124 was obtained on Sony, Appel, and Dell Alternatives to be recommended in the selection of laptops. Based on the results of the research, it can be concluded that the decision support system (SPK) with the Weighted Product (WP) method can provide laptop recommendations that suit the needs of users. This research provides benefits for users in choosing the right laptop that suits their needs. In addition, this research can also be the basis for the development of a decision support system for the selection of laptops or computers in other fields.

Authors

Institutions

Publication Details

Journal
TIERS Information Technology Journal
Published
2024-12-25
DOI
https://doi.org/10.38043/tiers.v5i2.6028
Primary Topic
Advanced Database Systems and Queries
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Decision Support System for Laptop Selection Recommendations Using the Weigted Product (WP) Method

Yelmi Yunarti, Jum Dapiokta, Johan Eka Wijaya, Joko Kuswanto et al.
TIERS Information Technology Journal
Advanced Database Systems and Queries
article

Decision Support System for Laptop Selection Recommendations Using the Weigted Product (WP) Method

Yelmi Yunarti, Jum Dapiokta, Johan Eka Wijaya, Joko Kuswanto, Anggeraeni Agustin Muris
article en

Abstract

The many types of specifications, colors and brands of laptops are complicated and confusing for ordinary people who are going to buy laptops. The reason is, there are many variants of laptops on the market with different specifications. To help potential consumers in choosing a laptop that suits their needs, a decision support system (SPK) is needed that can provide the most appropriate laptop recommendations. This study discusses the decision support system for laptop selection recommendations using the Weighted Product (WP) method. This method is used to help consumers choose a laptop that suits their needs based on predetermined criteria, such as processor, RAM, Storage, and Price. After a search of the vector to get the ranking, the largest vector value of 0.124 was obtained on Sony, Appel, and Dell Alternatives to be recommended in the selection of laptops. Based on the results of the research, it can be concluded that the decision support system (SPK) with the Weighted Product (WP) method can provide laptop recommendations that suit the needs of users. This research provides benefits for users in choosing the right laptop that suits their needs. In addition, this research can also be the basis for the development of a decision support system for the selection of laptops or computers in other fields.

TIERS Information Technology JournalVol. 5(2)
Universitas Baturaja (ID)
Openalex Percentile: Top 69%
Advanced Database Systems and Queries
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.