Jurnal of Applied Multimedia and Networking
Vol 8 No 2 (2024): Journal of Applied Multimedia and Networking

Analisis Perbandingan Render Engine Cycles & Eevee Pada Blender Melalui Metode Quasi- Monte Carlo Untuk Meningkatkan Rendering Di PT. Labtech Penta International

Timur Kanistren, Aragani (Unknown)
Liannardie, Muhammad (Unknown)



Article Info

Publish Date
08 Jan 2025

Abstract

This research focuses on analyzing the comparison between Cycles and Eevee render engines within the open-source software Blender 3D. The test results will assist PT. Labtech Penta International and users of three-dimensional applications in selecting the appropriate render engine for 3D model projects with still image outputs. The study aims to find configurations between Cycles and Eevee render engines or investigate them using the Quasi-Monte Carlo method, where the values or configurations in the settings of each render engine are tested using multiple samples. In each sample, the values or configurations are randomly adjusted. The measurement parameters for this test use three variables: rendering speed, size of the rendered file output, and image quality of the render result, taking into account the vertices and texture nodes on the 3D object. The results of this study indicate that Eevee outperforms Cycles in terms of rendering speed, while Cycles and Eevee produce similar file sizes in their render outputs. Regarding image quality, the results show that Cycles is superior to Eevee. The research aims to find a solution for rendering at PT. Labtech Penta International with stable and effective configurations.

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Journal Info

Abbrev

JAMN

Publisher

Subject

Arts Decision Sciences, Operations Research & Management Education Other

Description

Journal of Applied Multimedia and Networking (JAMN) is a journal published by Study Program of Multimedia and Networking, Politeknik Negeri Batam. The JAMN is issued 2 times a year in electronic form. The electronic pdf version is accessible on the internet free of charge. We encourage all ...