Recommendation System for Determining the Best Banner Supplier Using Profile Matching and TOPSIS Methods

Anik Vega Vitianingsih; Deden Firmansyah; Anastasia Lidya Maukar; Slamet Kacung; Hewa Majeed Zangana

doi:10.29407/intensif.v8i2.21635

Authors

Anik Vega Vitianingsih Universitas Dr.Soetomo Surabaya https://orcid.org/0000-0002-1651-1521
Deden Firmansyah Universitas Dr. Soetomo https://orcid.org/0009-0002-6577-777X
Anastasia Lidya Maukar Universitas Presiden https://orcid.org/0000-0002-5851-7454
Slamet Kacung Universitas Dr. Soetomo https://orcid.org/0009-0004-5032-5185
Hewa Majeed Zangana Duhok Polytechnic University https://orcid.org/0000-0001-7909-254X

DOI:

https://doi.org/10.29407/intensif.v8i2.21635

Keywords:

DSS, System Recommendation, Banner Supplier Selection, Profile Matching Method, TOPSIS Method, Performance Algorithm

Abstract

Background: Choosing a banner supplier is a significant challenge for digital printing companies due to the various advantages offered by each supplier, often leading to selections based on subjective aspects such as price and quality. Objective: This research aims to develop a system that determines the best banner supplier to minimize production inefficiencies and maximize profits by comparing two calculation methods, Profile Matching and TOPSIS. Methods: A quantitative study was conducted using transaction data from the last six months. The parameter criteria used in this system include price, quality, delivery, availability, and payment terms. The study compares the effectiveness of Profile Matching and TOPSIS methods in identifying the best supplier. Results: The study results show that the TOPSIS method is superior, yielding 100% accuracy, 84% recall, and a 92% F1-score, outperforming the Profile Matching method. This demonstrates that the correct method and algorithm effectively provide the best alternative recommendations. Conclusion: The results indicate that using the TOPSIS method leads to more accurate and objective decisions based on predetermined criteria. The findings suggest that further research should focus on refining these methods to enhance decision-making in supplier selection.

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Author Biographies

Anik Vega Vitianingsih, Universitas Dr.Soetomo Surabaya

Informatics Department, Universitas Dr. Soetomo, Surabaya, Indonesia

Deden Firmansyah, Universitas Dr. Soetomo

Informatics Department, Universitas Dr. Soetomo, Surabaya, Indonesia

Anastasia Lidya Maukar, Universitas Presiden

Department of Industrial Engineering,Universitas Presiden, Bekasi, Indonesia

Slamet Kacung, Universitas Dr. Soetomo

Informatics Department, Universitas Dr. Soetomo, Surabaya, Indonesia

Hewa Majeed Zangana, Duhok Polytechnic University

5IT Department, Duhok Technical College, Duhok Polytechnic University, Duhok, Iraq

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