Evaluation and Segmentation of Printing Accessories Suppliers Based on the Integration of the Best Worst Method and Fuzzy TOPSIS (Case Study at PT. Udaka Indonesia)

Authors

  • Wakhid Nur Hidayat Universitas Sarjanawiyata Tamansiswa
  • Elly Wuryaningtyas Yunitasari Universitas Sarjanawiyata Tamansiswa
  • Patrisius Edi Prasetyo Universitas Sarjanawiyata Tamansiswa

DOI:

https://doi.org/10.31315/opsi.v14i2.5312

Keywords:

Supplier evaluation, Supplier segmentation, Best Worst Method (BWM), Fuzzy TOPSIS

Abstract

In an increasingly competitive industrial environment, every company strives to increase the quality and efficiency of its product development process. PT. Udaka Indonesia, a clothing manufacturer, is experiencing raw material shortages that disrupt the company's production process. The goal of this research is to assess and segment the company's suppliers. The Best Worst Method (BWM) is employed for weighting criteria, and Fuzzy TOPSIS is used to rank alternative providers and subsequently segment them. The dimensions of capabilities (8 criteria with 26 sub-criteria) and willingness (4 criteria with 15 sub-criteria) make up the company's supplier evaluation criteria. The evaluation results suggest that suppliers A2, B2, C2, and D2 are the best in terms of capabilities for label accessories, stickers, paper tags, and polybags, respectively, while A1, B2, C2, and D2 are the best in terms of willingness. Supplier segmentation results show that segmentation 1 includes suppliers C1, B1, B3, and D1, segmentation 2 includes supplier A3, and segmentation 4 includes suppliers A1, A2, B2, B4, C2, and D2.

 

Author Biography

Elly Wuryaningtyas Yunitasari, Universitas Sarjanawiyata Tamansiswa

Industrial Engineering

References

Adhiana, T. P., Krisnawati, M., & Asyari, H. (2019). Evaluasi Kinerja Pemasok Bahan Baku Menggunakan Metode Fuzzy Promethee. Dinamika Rekayasa, 15(2), 107. https://doi.org/10.20884/1.dr.2019.15.2.271

Dachyar, M., & Maharani, A. K. (2019). Supplier evaluation and segmentation in cheese companies using the best-worst method and TOPSIS. Proceedings of the International Conference on Industrial Engineering and Operations Management, July, 81–89.

Gupta, H., & Barua, M. K. (2017). Supplier selection among SMEs based on their green innovation ability using BWM and fuzzy TOPSIS. Journal of Cleaner Production, 152, 242–258. https://doi.org/10.1016/j.jclepro.2017.03.125

Hendratmiko, Y. (2010). Analisis Pengendalian Persediaan Bahan Baku Pada Industri Kecil Menengah Mebel di Kota Kendal (Issue 1).

Kurniawan, V. R. B., & Puspitasari, F. H. (2021). A Fuzzy BWM Method for Evaluating Supplier Selection Factors in an SME Paper Manufacturer. IOP Conference Series: Materials Science and Engineering, 1071(1), 012004. https://doi.org/10.1088/1757-899x/1071/1/012004

Lestari, S., & Fauzi, C. (2019). Evaluasi Supplier Kemasan Dus Dengan Menerapkan Metode Analytical Hierarchy Process (Ahp) (Studi Kasus Di Pt Innovation). Journal Industrial Servicess, 4(2). https://doi.org/10.36055/jiss.v4i2.5153

Mokhtarian, M. N. (2015). A note on "extension of fuzzy TOPSIS method based on interval-valued fuzzy sets." Applied Soft Computing Journal, 26, 513–514. https://doi.org/10.1016/j.asoc.2014.10.013

Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega (United Kingdom), 53, 49–57. https://doi.org/10.1016/j.omega.2014.11.009

Rezaei, J., & Ortt, R. (2013). Multi-criteria supplier segmentation using a fuzzy preference relation-based AHP. European Journal of Operational Research, 225(1), 75–84. https://doi.org/10.1016/j.ejor.2012.09.037

Rezaei, J., Wang, J., & Tavasszy, L. (2015). Linking supplier development to supplier segmentation using Best Worst Method. Expert Systems with Applications, 42(23), 9152–9164. https://doi.org/10.1016/j.eswa.2015.07.073

Sulistyoningarum, R., Rosyidi, C. N., & Rochman, T. (2019). Supplier selection of recycled plastic materials using best worst and TOPSIS method. Journal of Physics: Conference Series, 1367(1). https://doi.org/10.1088/1742-6596/1367/1/012041

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Published

2021-12-21

Issue

Vol. 14 No. 2 (2021): ISSN 1693-2102

Section

Artikel

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