Enhancing Gaming Performance: A Recommender System for Selecting Optimal Gaming Headsets Based on SAW Method

Toruan, Bobby Chrismanto Lumban and Istiono, Wirawan (2023) Enhancing Gaming Performance: A Recommender System for Selecting Optimal Gaming Headsets Based on SAW Method. Journal of Advances in Mathematics and Computer Science, 38 (9). pp. 230-247. ISSN 2456-9968

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Abstract

Aims: The objective of this research is to design and develop a gaming headset recommendation system using the Simple Additive Weighting (SAW) algorithm based on a website. Additionally, the goal is to obtain user satisfaction ratings for the gaming headset recommendation system using the SAW algorithm, based on the End-User Computing Satisfaction (EUCS) model

Study Design: This study was designed with Simple Additive Weighting method to build a gaming headsets website

Place and Duration of Study: This study's respondents were recruited from the Edu Computer Store on Jl Citra Raya Boulevard, Cikupa, Tangerang, Indonesia. From January to June of 2023, and this study was conducted at Universitas Multimedia Nusantara.

Methodology: In this research, the method designed is the Simple Additive Weighting (SAW) method, which aims to facilitate users in making the right decisions regarding gaming headsets. The SAW method provides a straightforward approach for evaluating and comparing multiple criteria to assist users in their decision-making process.

Results: Based on the conducted test results, there is a user satisfaction rate of 83.35% based on the End User Computing Satisfaction (EUCS) model, indicating that users strongly agree with the system.

Conclusion: The gaming headset recommendation system has been successfully designed and built using the Simple Additive Weighting (SAW) method. This system functions to recommend gaming headsets based on the comparison of six criteria: weight, price, driver size, frequency response, impedance, and sensitivity, according to user preferences. The system is developed on a web platform using the PHP Laravel framework.

Item Type: Article
Subjects: STM Repository > Mathematical Science
Depositing User: Managing Editor
Date Deposited: 16 Oct 2023 07:33
Last Modified: 16 Oct 2023 07:33
URI: http://classical.goforpromo.com/id/eprint/4245

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