Decision Support System for Choosing the Best Shipping Service for E-Commerce Using the SAW and CRITIC Methods

Junhai Wang; Setiawansyah Setiawansyah; Yuri Rahmanto

doi:10.58602/jima-ilkom.v3i2.32

Junhai Wang Zhejiang Technical Institute of Economics
Setiawansyah Setiawansyah Universitas Teknokrat Indonesia
Yuri Rahmanto Universitas Teknokrat Indonesia

DOI: https://doi.org/10.58602/jima-ilkom.v3i2.32

Keywords: Combination, CRITIC, Decision, E-Commerce, SAW

Abstract

Choosing the best delivery service for e-commerce is a crucial step that can affect customer satisfaction and overall business success. In today's digital era, consumers expect fast, secure, and affordable delivery. The main problem in choosing the best shipping service for e-commerce is often related to several interrelated factors, which can affect the customer experience and business sustainability. One of the biggest challenges is ensuring that products reach customers within the promised time. Delays in delivery can lead to customer dissatisfaction and potentially damage a business's reputation. The combination of SAW and CRITIC methods provides a powerful approach to multi-criteria decision-making. By leveraging the advantages of each method, users can objectively determine the weight of the criteria and evaluate alternatives in a systematic and transparent way. This approach not only improves the accuracy of decisions but also increases decision-makers confidence in the results obtained. Based on the results of the ranking using the method that has been applied, the alternative with the highest score is Pos Indonesia (A6) with a final score of 0.82506, followed by JNE (A1) with a score of 0.76181, and Tiki (A2) with a score of 0.72127. Based on these values, Pos Indonesia ranks first as the best service provider.

Downloads

Download data is not yet available.

References

J. Wang and G. Zheng, “Research on E-commerce Talents Training in Higher Vocational Education under New Business Background,” INTI J., vol. 2020, no. 5, 2020.

J. Wang, “Impact of mobile payment on e-commerce operations in different business scenarios under cloud computing environment,” Int. J. Syst. Assur. Eng. Manag., vol. 12, no. 4, pp. 776–789, Aug. 2021, doi: 10.1007/s13198-021-01100-3.

J. Wang and Y. Zhang, “Using cloud computing platform of 6G IoT in e-commerce personalized recommendation,” Int. J. Syst. Assur. Eng. Manag., vol. 12, no. 4, pp. 654–666, Aug. 2021, doi: 10.1007/s13198-021-01059-1.

P. Palupiningsih and S. Setiawansyah, “Best Sales Selection Using a Combination of Reciprocal Rank Weighting Method and Multi-Attribute Utility Theory,” J. Comput. Informatics Res., vol. 3, no. 3, pp. 242–250, Jul. 2024, doi: 10.47065/comforch.v3i3.1496.

O. Kabadurmus, Y. Kayikci, S. Demir, and B. Koc, “A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks,” Socioecon. Plann. Sci., vol. 85, p. 101417, 2023.

R. Nuari, S. Setiawansyah, and M. Mesran, “Penerapan Sistem Pendukung Keputusan Pemilihan Cleaning Servis Terbaik Menggunakan Kombinasi Metode Pembobotan Entropy dan COPRAS,” Build. Informatics, Technol. Sci., vol. 6, no. 2, pp. 1169–1180, 2024, doi: 10.47065/bits.v6i2.5796.

C. Z. Radulescu and M. Radulescu, “A Hybrid Group Multi-Criteria Approach Based on SAW, TOPSIS, VIKOR, and COPRAS Methods for Complex IoT Selection Problems,” Electronics, vol. 13, no. 4, p. 789, Feb. 2024, doi: 10.3390/electronics13040789.

E. Rahmayana, “Penerapan Metode Simple Additive Weighting (SAW) dan Rank Order Centroid Dalam Analisis Kinerja Pegawai Honorer,” Resolusi Rekayasa Tek. Inform. dan Inf., vol. 4, no. 5, pp. 494–501, 2024.

Juanda, S. Hartuti, and R. Agustina, “Effect of microwave heating on sensory quality assessment of butterfly pea (Clitoria ternatea L.) flower using simple additive weighting,” IOP Conf. Ser. Earth Environ. Sci., vol. 1290, no. 1, p. 012020, Jan. 2024, doi: 10.1088/1755-1315/1290/1/012020.

L. Zhang, Q. Cheng, and S. Qu, “Evaluation of Railway Transportation Performance Based on CRITIC-Relative Entropy Method in China,” J. Adv. Transp., vol. 2023, pp. 1–11, Mar. 2023, doi: 10.1155/2023/5257482.

T. Van Dua, D. Van Duc, N. C. Bao, and D. D. Trung, “Integration of objective weighting methods for criteria and MCDM methods: application in material selection,” EUREKA Phys. Eng., no. 2, pp. 131–148, Mar. 2024, doi: 10.21303/2461-4262.2024.003171.

Marković, Stajić, Stević, Mitrović, Novarlić, and Radojičić, “A Novel Integrated Subjective-Objective MCDM Model for Alternative Ranking in Order to Achieve Business Excellence and Sustainability,” Symmetry (Basel)., vol. 12, no. 1, p. 164, Jan. 2020, doi: 10.3390/sym12010164.

M. W. Arshad, S. Setiawansyah, R. R. Suryono, and Y. Rahmanto, “Combination of CRITIC Weighting Method and Multi-Atributive Ideal-Real Comparative Analysis in Staff Admissions,” Explorer (Hayward)., vol. 4, no. 2, pp. 77–86, 2024, doi: 10.47065/explorer.v4i2.1428.

M. N. D. Satria, S. Setiawansyah, and M. Mesran, “Combination of CRITIC Weighting Method and Multi-Attribute Utility Theory in Network Vendor Selection,” Build. Informatics, Technol. Sci., vol. 6, no. 1, pp. 188–197, 2024, doi: 10.47065/bits.v6i1.5342.

A. R. Paramanik, S. Sarkar, and B. Sarkar, “OSWMI: An objective-subjective weighted method for minimizing inconsistency in multi-criteria decision making,” Comput. Ind. Eng., vol. 169, p. 108138, 2022, doi: https://doi.org/10.1016/j.cie.2022.108138.