ANALISIS META SENJATA PADA PERMAINAN FIRST PERSON SHOOTER VALORANT MENGGUNAKAN ALGORITMA K-MEDIAN

HUTAGALUNG, MUHAMMAD AL-HAFIZ AKBAR and Arsalan, Osvari and Primanita, Anggina (2024) ANALISIS META SENJATA PADA PERMAINAN FIRST PERSON SHOOTER VALORANT MENGGUNAKAN ALGORITMA K-MEDIAN. Undergraduate thesis, Sriwijaya University.

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Abstract

This research aims to analyze weapon meta in the First Person Shooter (FPS) game Valorant using the K-Median algorithm. This algorithm is applied to cluster weapons based on performance parameters such as Average Damage per Round (ADR) and Average Combat Score (ACS). The clustering results show that the K-Median algorithm produces groupings more resilient to outliers compared to other algorithms. This study successfully recommends the most effective weapons to support players in winning rounds. The designed system assists players, especially beginners, in selecting weapons based on statistical data from the Valorant Champions Tour (VCT) 2021 tournament. Therefore, this research significantly contributes to the development of decision support systems in competitive gaming

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Valorant, K-Median, Clustering, Meta Senjata, FPS
Subjects:	Q Science > Q Science (General) > Q1-295 General
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Muhammad Al-Hafiz Akbar Hutagalung
Date Deposited:	13 Jan 2025 04:44
Last Modified:	13 Jan 2025 04:44
URI:	http://repository.unsri.ac.id/id/eprint/164101

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