Sistem Pendukung Keputusan Pemilihan E-Commerce Menggunakan Pembobotan Entropy dan COPRAS

Puspa Citra; Heri Bambang Santoso; I Wayan Sriyasa

doi:10.58602/jima-ilkom.v3i1.25

Puspa Citra Universitas Pakuan
Heri Bambang Santoso Universitas Pakuan
I Wayan Sriyasa Universitas Pakuan

DOI: https://doi.org/10.58602/jima-ilkom.v3i1.25

Keywords: COPRAS, E-commerce, Entropy, Platform, Recommendations

Abstract

The choice of e-commerce platform is crucial for businesses that want to expand their reach and increase sales online. By choosing the right e-commerce platform, businesses can optimize their online operations, increase customer satisfaction, and achieve sustainable growth in an increasingly competitive digital marketplace. This study aims to select e-commerce using a combination of entropy weighting methods and COPRAS in producing alternative assessments and ratings of existing e-commerce, so that it becomes a recommendation for the public in choosing an e-commerce as a transaction platform. The ranking results in the final e-commerce score are rank 1 obtained for Shoope e-commerce with a value of 100%, rank 2 obtained for Tokopedia e-commerce with a value of 95.93%, rank 3 obtained for Lazada e-commerce with a value of 80.93%, and rank 4 obtained for Blibli e-commerce with a value of 58.07%. The recommendation results for selecting an E-Commerce platform using a combination of Entropy and COPRAS weighting methods provide the highest recommendation to the Shoope E-Commerce platform with the highest value of 100%.

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References

[1] W. M. Sari, A. Amran, and H. O. L. Wijaya, “PENERAPAN E-COMMERCE MENGGUNAKAN METODE EXTREME PROGRAMMING PADA UMKM KABUPATEN MURATARA,” Jusikom J. Sist. Komput. Musirawas, vol. 5, no. 2, pp. 136–144, 2020.
[2] Z. Azhar, N. Mulyani, J. Hutahaean, and A. Mayhaky, “Sistem Pendukung Keputusan Pemilihan E-Commerce Terbaik Menggunakan Metode MOOSRA,” J. MEDIA Inform. BUDIDARMA, vol. 6, no. 4, pp. 2346–2351, 2022.
[3] E. Fitria and G. Gunawan, “Penerapan Metode MOOSRA pada Sistem Pendukung Keputusan Pemilihan E-commerce dalam Pembelian Produk Fashion,” J. Ris. Mat., pp. 55–64, 2023.
[4] A. Wantoro, “Kombinasi Metode Analitical Hierarchy Process (Ahp) Dan Simple Addtive Weight (Saw) Untuk Menentukan Website E-Commerce Terbaik,” Sistemasi, vol. 9, no. 1, p. 131, 2020, doi: 10.32520/stmsi.v9i1.608.
[5] S. H. Hadad et al., “Student Ranking Based on Learning Assessment Using the Simplified PIPRECIA Method and CoCoSo Method,” J. Comput. Syst. Informatics, vol. 5, no. 1, 2023, doi: 10.47065/josyc.v5i1.4544.
[6] S. Setiawansyah, A. Surahman, A. T. Priandika, and S. Sintaro, Penerapan Sistem Pendukung Keputusan pada Sistem Informasi. Bandar Lampung: CV Keranjang Teknologi Media, 2023. [Online]. Available: https://buku.techcartpress.com/detailebook?id=1/penerapan-sistem-pendukung-keputusan-pada-sistem-informasi/setiawansyah-ade-surahman-adhie-thyo-priandika-sanriomi-sintaro
[7] T. Widodo, “Penerapan Metode Complex Proportional Assessment Dalam Penentuan Ketua Karang Taruna,” J. Ilm. Comput. Sci., vol. 1, no. 2, pp. 88–98, 2023, doi: 10.58602/jics.v1i2.10.
[8] P. Citra, “Penerapan Metode Complex Proportional Assessment (COPRAS) Pada Penilaian Kelayakan Produk,” J. Data Sci. Inf. Syst., vol. 1, no. 4, pp. 150–158, 2023.
[9] A. Fathurrozi, A. Damuri, A. T. Prastowo, and Y. Rahmanto, “Sistem Pendukung Keputusan Pemilihan Lahan Tanaman Kopi Menggunakan Metode Complex Proportional Assessment (COPRAS),” KLIK Kaji. Ilm. Inform. dan Komput., vol. 3, no. 3, pp. 228–237, 2022.
[10] S. Kayapinar Kaya and E. Aycin, “An integrated interval type 2 fuzzy AHP and COPRAS-G methodologies for supplier selection in the era of Industry 4.0,” Neural Comput. Appl., vol. 33, no. 16, pp. 10515–10535, 2021.
[11] A. D. U. Siregar, N. A. Hasibuan, and F. Fadlina, “Sistem Pendukung Keputusan Pemilihan Sales Marketing Terbaik di PT. Alfa Scorph Menggunakan Metode COPRAS,” J. Sist. Komput. dan Inform., vol. 2, no. 1, pp. 62–68, 2020.
[12] A. Surahman, “Penilaian Kinerja Karyawan Menggunakan Kombinasi Metode Multi-Objective Optimization by Ratio Analysis (MOORA) dan Pembobotan Entropy,” Chain J. Comput. Technol. Comput. Eng. Informatics, vol. 2, no. 1, pp. 28–36, 2024.
[13] S. Setiawansyah, “Penerapan Metode Entropy dan Grey Relational Analysis dalam Evaluasi Kinerja Karyawan,” J. Data Sci. Inf. Syst., vol. 2, no. 1, pp. 29–39, 2024, doi: 10.58602/dimis.v2i1.100.
[14] D. D. Trung and H. X. Thinh, “A multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study,” Adv. Prod. Eng. Manag., vol. 16, no. 4, pp. 443–456, Dec. 2021, doi: 10.14743/apem2021.4.412.
[15] J. Fan, J. Liu, S. Xie, C. Zhou, and Y. Wu, “Cervical lesion image enhancement based on conditional entropy generative adversarial network framework,” Methods. Elsevier BV, 2021. doi: 10.1016/j.ymeth.2021.11.004.
[16] A. Ahyuna, B. Rahman, F. Nugroho, I. W. S. Nirawana, and A. Karim, “Analisa Penerapan Metode MABAC dengan Pembobotan Entropy dalam Penilaian Kinerja Dosen di Era Society 5.0,” Build. Informatics, Technol. Sci., vol. 5, no. 1, pp. 29–39, 2023.