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Journal : Journal Electrical and Computer Experiences

Determining Participants in the Web Technologies Student Competency Competition Using the Vikor Method Maulia Rahman
Journal Electrical and Computer Experiences Vol. 1 No. 2 (2023): July-December
Publisher : Tinta Emas Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59535/jece.v1i2.201

Abstract

The selection of participants in the student competency competition (LKS) of SMK Swasta Tritech Informatika Medan is done manually by collecting students, calculating and comparing with supporting data such as the average competency score in the report by productive teachers. In order to be more efficient and right on target in selecting students as participants in the student competency competition at SMKS Tritech Informatika Medan, the head of the department must change the system. The application of the VIKOR method is used in determining the order or priority in efficient and simple multicriteria analysis. Based on the research sample data, with the lowest Qi result score, namely value 0, selected as a participant in the Student Competency Competition (LKS) which will represent the SMK Tritech Informatika Medan school for the Software Engineering and Game Department, namely alternative A8 with the student's name Nafil Rizqtrianto with 6 criteria, namely Mastering programming languages, Understanding Framework, Understanding program analysis, Understanding OOP, Mastering databases and report card scores.
Comparative Analysis of AHP and TOPSIS Methods in Retail Business Location Selection Decision Support System Maulia Rahman
Journal Electrical and Computer Experiences Vol. 2 No. 2 (2024): July-December
Publisher : Tinta Emas Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59535/jece.v2i2.355

Abstract

Retail business location selection is a critical strategic decision for company success. This research aims to compare the effectiveness of the Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods in decision support systems for retail business location selection. Using a simulation-based quantitative approach, this study evaluates the performance of both methods based on alternative ranking accuracy, result consistency, and computational efficiency. Results show that AHP excels in handling complex criteria hierarchies and result consistency, while TOPSIS demonstrates superiority in computational efficiency and resilience to data outliers. Sensitivity analysis reveals that AHP is more sensitive to changes in criteria weights compared to TOPSIS. Model validation through comparison with literature case studies shows a high level of concordance between simulation results and actual decisions. This research provides theoretical contributions to the development of decision support systems and practical implications for decision-makers in the retail industry. Development prospects include method integration for hybrid approaches and exploration of big data integration in the retail location decision-making process.