Penerapan Metode G-MAUT Dalam Pemilihan Editor Video Terbaik

Ade Dwi Putra; M. Ghufroni An’ars

doi:10.58602/itsecs.v2i4.161

Ade Dwi Putra Universitas Teknokrat Indonesia
M. Ghufroni An’ars Universitas Teknokrat Indonesia

DOI: https://doi.org/10.58602/itsecs.v2i4.161

Keywords: G-MAUT, Objective, Election, Ranking, Video Editor

Abstract

A video editor is a professional who is responsible for processing raw footage into videos that are interesting, structured, and in accordance with the project's objectives. Choosing the best video editor requires careful consideration to evaluate their mastery of popular editing software, as well as additional capabilities such as color correction, audio processing, and visual effects. The main problem in choosing the best video editor often has to do with the difficulty of objectively assessing quality and ability before working together. Problems in the best video editor rating often arise due to the subjective nature of the work and depend on aesthetic preferences as well as the specific needs of the project. This study aims to apply the G-MAUT method in the process of selecting the best video editor. The main goal is to produce an objective, systematic, and multi-criteria-based assessment system to help make more accurate decisions. By using the G-MAUT method, this research can provide solutions that can improve efficiency and fairness in the election process, as well as contribute to the development of decision support systems in the creative field. The results of the calculation using the G-MAUT method in the ranking of the best video editor selection were obtained by Candidate C managed to rank first with the highest final score, which was 0.7794, showing superior performance compared to other candidates. In second place, there is Candidate A with a score of 0.4241, which still shows a significant contribution even though it is quite far from the first place. Candidate D followed in third place with a score of 0.3573. These results illustrate the stark differences among the candidates, providing important insights for further evaluation.

References

R. Y. Lubis, M. Syahril, and S. Sobirin, “Pemilihan Editor Berita Terbaik Menggunakan Metode Complex Proportional Assessment (COPRAS),” J. Cyber Tech, vol. 3, no. 4, pp. 738–747, 2020.

A. T. Priandika et al., “Video Editing Training to Improve the Quality of Teaching and Learning at SMK Palapa Bandarlampung,” J. Eng. Inf. Technol. Community Serv., vol. 1, no. 2, pp. 26–30, 2022.

V. R. Campos and D. J. S. Moreira, “Risk assessment with multi-attribute utility theory for building projects,” J. Build. Pathol. Rehabil., vol. 7, no. 1, p. 98, 2022.

U. Akpan and R. Morimoto, “An application of Multi-Attribute Utility Theory (MAUT) to the prioritization of rural roads to improve rural accessibility in Nigeria,” Socioecon. Plann. Sci., vol. 82, p. 101256, 2022.

J. H. Lubis, M. Mesran, and C. A. Siregar, “The Decision Support System for Cashier Recruitment Implements the Multi-Attribute Utility Theory Method,” Build. Informatics, Technol. Sci., vol. 6, no. 1, pp. 257–264, 2024.

Z. Allah Bukhsh, I. Stipanovic, and A. G. Doree, “Multi-year maintenance planning framework using multi-attribute utility theory and genetic algorithms,” Eur. Transp. Res. Rev., vol. 12, no. 1, pp. 1–13, 2020.

I. Oktaria, “Kombinasi Metode Multi-Attribute Utility Theory (MAUT) dan Rank Order Centroid (ROC) dalam Pemilihan Kegiatan Ekstrakulikuler,” J. Ilm. Inform. dan Ilmu Komput., vol. 2, no. 1, pp. 1–11, 2023.

W. Saputra, S. A. Wardana, H. Wahyuda, and D. A. Megawaty, “Penerapan Kombinasi Metode Multi-Attribute Utility Theory (MAUT) dan Rank Sum Dalam Pemilihan Siswa Terbaik,” J. Inf. Technol. Softw. Eng. Comput. Sci., vol. 2, no. 1, pp. 12–21, 2024.

Y. Harefa, F. T. Waruwu, and M. Sayuti, “Implementasi Metode MAUT Dengan Pembobotan ROC Pada Sistem Pendukung Keputusan Pemilihan Kepala Gudang PT. Sinwa Perdana Mandiri,” KETIK J. Inform., vol. 1, no. 02, pp. 1–10, 2023.

S. Setiawansyah and Y. Rahmanto, “Implementation of the Geometric Mean Multi-Attribute Utility Theory (G-MAUT) in Determining the Best Honorary Employees,” J. Ilm. Comput. Sci., vol. 3, no. 2 SE-Articles, pp. 111–119, Jan. 2025, doi: 10.58602/jics.v3i2.50.

M. W. Arshad, S. Setiawansyah, Y. Rahmanto, P. Palupiningsih, and S. Maryana, “Modification of Multi-Attribute Utility Theory in Determining Scholarship Recipient Students,” BEES Bull. Electr. Electron. Eng., vol. 5, no. 1, pp. 10–19, 2024, doi: 10.47065/bees.v5i1.5523.

H. Sulistiani, Setiawansyah, P. Palupiningsih, F. Hamidy, P. L. Sari, and Y. Khairunnisa, “Employee Performance Evaluation Using Multi-Attribute Utility Theory (MAUT) with PIPRECIA-S Weighting: A Case Study in Education Institution,” in 2023 International Conference on Informatics, Multimedia, Cyber and Informations System (ICIMCIS), 2023, pp. 369–373. doi: 10.1109/ICIMCIS60089.2023.10349017.

E. R. Susanto, A. Savitri Puspaningrum, and Z. Abidin, “Recommendations of Cash Social Assistance (BST) Recipients for People Affected by Covid-19 Using AHP-TOPSIS,” in 2023 International Conference on Networking, Electrical Engineering, Computer Science, and Technology (IConNECT), Aug. 2023, pp. 190–195. doi: 10.1109/IConNECT56593.2023.10326776.

A. D. Wahyudi, “Penentuan Lokasi Gudang Baru Menggunakan TOPSIS dan Pembobotan PIPRECIA,” J. Inf. Technol. Softw. Eng. Comput. Sci., vol. 2, no. 1, pp. 22–30, 2024.

A. T. Priandika and D. Riswanda, “Perancangan Sistem Informasi Manajemen Pemesanan Barang Berbasis Online Menggunakan Pendekatan Extreme Programming,” J. Ilm. Comput. Sci., vol. 1, no. 2, pp. 69–76, 2023, doi: 10.58602/jics.v1i2.8.