Sistem Pendukung Keputusan untuk Pemilihan Jasa Pengiriman Terbaik pada Bisnis Online Menggunakan Metode SMART dan ROC
Abstract
Delivery services are services that provide logistics solutions to deliver goods or documents from one location to another efficiently and on time. The main problem in choosing the best delivery service lies in the complexity of assessing various criteria that affect the quality of service. In addition, the information available from service providers is often subjective and does not reflect actual performance, hindering objective decision-making. The choice of delivery service can also be affected by the lack of accurate information about the service's performance, especially if customers only rely on reviews or recommendations that do not necessarily reflect the true quality. In addition, the selection based on the cheapest price without considering the quality aspect can risk the safety and timeliness of delivery of goods. As a result of calculating the utility value using the SMART method, the best delivery service alternative for online businesses is Jasa C, which obtained the highest utility value of 0.9100, making it the first choice in the ranking. In second place, there is Jasa E with a utility value of 0.5548, which shows a fairly good performance although not as high as Jasa C. Jasa A follows in third place with a utility value of 0.4778, which indicates that this alternative has a lower performance than the top two delivery services. The results of this ranking provide a clear picture of the performance of each delivery service, which can be used as a basis for decision-making to choose the optimal delivery service according to the needs of online business.
References
J. Wang, D. Darwis, S. Setiawansyah, and Y. Rahmanto, “Implementation of MABAC Method and Entropy Weighting in Determining the Best E-Commerce Platform for Online Business,” JiTEKH, vol. 12, no. 2, pp. 58–68, 2024, doi: 10.35447/jitekh.v12i2.1000.
J. H. Lubis, M. Mesran, and C. A. Siregar, “The Decision Support System for Cashier Recruitment Implements the Multi-Attribute Utility Theory Method,” Build. Informatics, Technol. Sci., vol. 6, no. 1, pp. 257–264, 2024.
D. Tešić, M. Radovanović, D. Božanić, D. Pamucar, A. Milić, and A. Puška, “Modification of the DIBR and MABAC Methods by Applying Rough Numbers and Its Application in Making Decisions,” Information, vol. 13, no. 8, p. 353, Jul. 2022, doi: 10.3390/info13080353.
D. Pamucar and S. Biswas, “A Novel Hybrid Decision Making Framework for Comparing Market Performance of Metaverse Crypto Assets,” Decis. Mak. Adv., vol. 1, no. 1, pp. 49–62, Dec. 2023, doi: 10.31181/dma1120238.
J. Wang, S. Setiawansyah, and Y. Rahmanto, “Decision Support System for Choosing the Best Shipping Service for E-Commerce Using the SAW and CRITIC Methods,” J. Ilm. Inform. dan Ilmu Komput., vol. 3, no. 2, pp. 101–109, 2024, doi: 10.58602/jima-ilkom.v3i2.32.
S. H. Hadad, “Analisis Prioritas Pemberian Cuti Karyawan Menggunakan Metode Pembobotan Entropy dan Simple Multi Attribute Rating Technique,” J. Artif. Intell. Technol. Inf., vol. 2, no. 2, pp. 106–117, 2024, doi: 10.58602/jaiti.v2i2.126.
S. Surati, S. Siswanti, and A. Kusumaningrum, “Metode Simple Multi Attribute Rating Technique Untuk Sistem Pendukung Keputusan Penentuan Penerima Beasiswa,” J. Ilm. SINUS, vol. 20, no. 2, pp. 57–66, 2022.
H. I. Santoso, “Seleksi Penerimaan Programmer Menggunakan Simple Multi Attribute Rating Technique Method (SMART Method) dan Rank Order Centroid,” J. Inf. Technol. Softw. Eng. Comput. Sci., vol. 2, no. 1, pp. 31–39, 2024.
S. Motamed, P. Rogalla, and F. Khalvati, “RANDGAN: Randomized generative adversarial network for detection of COVID-19 in chest X-ray,” Scientific Reports, vol. 11, no. 1. Springer Science and Business Media LLC, 2021. doi: 10.1038/s41598-021-87994-2.
K. Blind, F. Ramel, and C. Rochell, “The influence of standards and patents on long-term economic growth,” J. Technol. Transf., vol. 47, no. 4, pp. 979–999, 2022.
Y. A. Prasetyo and P. A. R. Devi, “Implementasi Metode SAW dengan Pembobotan ROC dalam Menentukan Teknisi Terbaik pada PT. KAS,” Ilk. J. Comput. Sci. Appl. Informatics, vol. 4, no. 3, pp. 316–326, 2022, doi: 10.28926/ilkomnika.v4i3.524.
J. Wang, A. R. Isnain, R. R. Suryono, Y. Rahmanto, M. Mesran, and S. Setiawansyah, “Decision Support System for Platform Selection in E-Commerce Using the OWH-TOPSIS Method,” J. Comput. Syst. Informatics, vol. 6, no. 1, pp. 172–181, 2024, doi: 10.47065/josyc.v6i1.5990.
Z. H. Ramadhani, N. A. Hasibuan, and D. P. Utomo, “Implementasi Metode MOORA Dengan Pembobotan Rank Order Centroid (ROC) dalam Seleksi Penerimaan Staff Gudang PT. Royal Abadi Sejahtera,” Build. Informatics, Technol. Sci., vol. 4, no. 2, pp. 581–587, Sep. 2022, doi: 10.47065/bits.v4i2.2073.
A. R. Mishra, A. K. Garg, H. Purwar, P. Rana, H. Liao, and A. Mardani, “An Extended Intuitionistic Fuzzy Multi-Attributive Border Approximation Area Comparison Approach for Smartphone Selection Using Discrimination Measures,” Informatica, vol. 32, no. 1, pp. 119–143, Oct. 2021, doi: 10.15388/20-INFOR430.
Z. Ardian, A. C. Alhadi, and G. M. Panji, “Employee performance assessment system based on smart method (case study: Banda Aceh Military Court I-01),” in AIP Conference Proceedings, 2023, vol. 2484, no. 1, p. 060022. doi: 10.1063/5.0113638.
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