Sistem Prediksi Keuntungan Influencer Pengguna E-Commerce Shopee Affiliates menggunakan Metode Naïve Bayes

Susanti Susanti, Aisum Aliyah Sari, M. Khairul Anam, Muhamad Jamaris, Hamdani Hamdani

Abstract


Shopee Affiliate is one of Shopee's e-commerce programs to make it easier to market products. However, with the popularity of this program, there are still many people who do not know the advantages of this program. As a result, in this e-commerce, not all sellers benefit (loss) from the products sold. In order to avoid the problem of losses on marketed products, this study aims to produce a profit prediction system for shoppe affiliate e-commerce users. To build the system, this research uses the waterfall method which is used to complete the prediction system. The first stage is to collect data from social media and references related to the prediction system, then design a prediction system, after carrying out the process of system creation and implementation and testing. The test uses blackbox to test the system and accuracy test to determine the level of accuracy of this system. The result of this prediction system is to gain knowledge in the form of profit rate patterns of influencers of shopee affiliate e-commerce users. Testing the accuracy of the system built has a very good performance with a percentage of 100%. So that the profit prediction of shopee affiliate e-commerce users is feasible to be implemented. With this system, it is hoped that the community will be able to increase sales at e-commerce shopee.


Keywords


e-commerce; influencer; naive bayes; prediction system; shopee affiliates

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References


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DOI: https://doi.org/10.29408/edumatic.v6i2.6787

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