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All Journal Jurnal Armada Informatika Journal of Embedded Systems, Security and Intelligent Systems
Lince Tomoria Sianturi
STMIK Mulia Darma
Computer Science & IT Control & Systems Engineering

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Decision Support System Integrating Entropy Weighting and MARCOS Ranking for Multi-Criteria Data-Driven Prioritization Lince Tomoria Sianturi; Berto Nadeak; Asyahri Hadi Nasyuha; Moses Adeolu Agoi
Journal of Embedded Systems, Security and Intelligent Systems Vol 7 No 2 (2026): June 2026
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/r0d49p45

Abstract

Purpose – This study aims to develop a data-driven decision support system that integrates entropy-based objective weighting with the MARCOS ranking method to improve multi-criteria prioritization in credit risk assessment by enhancing objectivity, consistency, and robustness of decision-making outcomes. Design/methods/approach – A hybrid MCDM framework is proposed, combining entropy weighting to determine criterion importance based on data variability and the MARCOS method to rank alternatives relative to ideal and anti-ideal solutions. The approach is evaluated using the Statlog German Credit dataset consisting of 1,000 applicants and six evaluation criteria. Performance is assessed through comparative analysis with conventional methods (TOPSIS and VIKOR), sensitivity testing under weight perturbation, and stability analysis using Spearman rank correlation. Findings - The results demonstrate that the proposed Entropy–MARCOS framework produces reliable and consistent prioritization outcomes. The model achieves a high ranking stability with a Spearman correlation of 0.91 and outperforms conventional MCDM methods in terms of ranking consistency. The findings also indicate that criteria such as age and employment duration have the highest discriminative importance, and the method remains robust under moderate variations in criterion weights. Research implications/limitations – However, the evaluation is limited to a single dataset and static criteria weights, which may affect generalizability across different domains or dynamic environments. Future research should explore adaptive weighting mechanisms and validate the model on more diverse datasets. Originality/value – This research contributes a unified hybrid framework that combines entropy-based objective weighting with the MARCOS ranking method, providing a more transparent, data-driven, and stable approach for multi-criteria decision-making, particularly in credit risk prioritization contexts.
User Experience Evaluation of Shopee-Based Product Sales at PT. Herba Hero Harmoni Using UEQ Adira Arifandi; Melissa Putri Hutabarat; Lince Tomoria Sianturi; Chandra Frenki Sianturi
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.276

Abstract

The development of digital technology encourages companies to use marketplaces as online sales and marketing channels. PT Herba Hero Harmoni uses the Shopee marketplace to support the sales of herbal products to customers. This study aims to evaluate the user experience of the online sales information system through the Shopee marketplace using the User Experience Questionnaire (UEQ) method. The study applied a quantitative descriptive approach involving 30 active Shopee users as respondents. Data were collected using the UEQ questionnaire, which consists of 26 items and six dimensions: attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty. The data were analyzed using the UEQ method and tested for validity and reliability. The validity test showed that 17 items were valid and 9 items were invalid. The reliability test obtained a Cronbach's Alpha value of 0.838, indicating that the instrument was reliable. The UEQ analysis showed average scores of 6.32 for attractiveness, 6.11 for perspicuity, 6.24 for efficiency, 6.05 for dependability, 6.38 for stimulation, and 5.96 for novelty. Stimulation achieved the highest score, while novelty achieved the lowest score but remained in the good category. Overall, the Shopee application provides a good to very good user experience and supports comfort, ease of use, and user satisfaction in online sales and purchase transactions.
Co-Authors Adira Arifandi Asyahri Hadi Nasyuha Berto Nadeak Chandra Frenki Sianturi Melissa Putri Hutabarat Moses Adeolu AGOI