Enhancing Gaming Performance: A Recommender System for Selecting Optimal Gaming Headsets Based on SAW Method
Bobby Chrismanto Lumban Toruan
Universitas Multimedia Nusantara, Jl. Scientia Boulevard, Curug Sangereng, Tangerang, Banten 15810, Indonesia.
Wirawan Istiono *
Universitas Multimedia Nusantara, Jl. Scientia Boulevard, Curug Sangereng, Tangerang, Banten 15810, Indonesia.
*Author to whom correspondence should be addressed.
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.
Keywords: Gaming headset recommendations, simple additive weighting, enduser computing satisfaction, decision support system