Metode Alternatif dalam Pencarian Peringkat E-Commerce di Indonesia Berdasarkan Rating Pelanggan

Authors

  • Azira Irawan Department of Statistics, IPB University, Indonesia
  • Aam Alamudi Department of Statistics, IPB University, Indonesia
  • Septian Rahardiantoro Department of Statistics, IPB University, Indonesia

DOI:

https://doi.org/10.29244/xplore.v10i1.280

Keywords:

ant colony optimization, analytical hierarchy process, e-commerce, rating

Abstract

The existence of the internet raises an online trading system using applications. The rise of online trading systems has triggered the emergence of various e-commerce in Indonesia that provide various kinds of customer needs. This also causes problems for customers, namely the difficulty in choosing quality e-commerce. The effort to overcome this problem is to rank e-commerce in Indonesia based on customer ratings. The method commonly used for ranking is the analytical hierarchy process (AHP) method, but in practice there are several variables that are not found in e-commerce so the AHP method cannot be used. The alternative method chosen is the ant colony optimization (ACO) method. The feasibility test of the ACO method in searching rankings for e-commerce data needs to be done because not all variables are in e-commerce. Simulations for ranking search are carried out using 2 generated data scenario with analytical hierarchy process (AHP) and ant colony optimization (ACO) method. The simulation results show that the ACO method is feasible to be used for ranking with blank data, then the application of the ACO method for e-commerce data in Indonesia. The best taboo results are based on the highest opportunity value and the highest correlation coefficient, namely in the second taboo, with three major ratings, namely JD, SP, and TP

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Published

2021-01-01

How to Cite

Irawan, A., Alamudi, A., & Rahardiantoro, S. (2021). Metode Alternatif dalam Pencarian Peringkat E-Commerce di Indonesia Berdasarkan Rating Pelanggan. Xplore: Journal of Statistics, 10(1), 27–40. https://doi.org/10.29244/xplore.v10i1.280

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