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Arya Fauzan Adima
Universitas Teknokrat Indonesia, Bandar Lampung
Computer Science & IT

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Kombinasi Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) dan Simple Additive Weighting (SAW) Pada Sistem Pendukung Keputusan Seleksi Magang Arya Fauzan Adima; Parjito Parjito
Bulletin of Computer Science Research Vol. 6 No. 3 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i3.1071

Abstract

The internship selection process at XZ University is still carried out conventionally, thus reducing time efficiency in decision making. The purpose of this study is to design a web-based Decision Support System (DSS) by applying a combination of Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) and Simple Additive Weighting (SAW) methods to increase the objectivity and efficiency of the selection process. The MOORA method functions to normalize and optimize alternative values as the basis for calculating SAW in internship selection, while the SAW method is used for normalizing and ranking alternatives based on weight criteria. This study uses a quantitative approach with a descriptive experimental method. Data were obtained through observation, interviews, and documentation. The criteria used include GPA, semester, collaboration time, video editing skills, camera operating skills, photography skills, videography skills, graphic design skills, creativity, attitude, discipline, responsibility. The results of data processing show that the five best alternatives with the highest preference values are A24 (100%), A3 (97%), A9 (96%), A5 (95%), dan A22 (93%.). These results show that the combination of the MOORA and SAW methods is able to provide the best alternative recommendations objectively and structured in the internship selection process.
Co-Authors Parjito Parjito