Jurnal Informatika dan Rekayasa Perangkat Lunak
Vol. 6 No. 2 (2024): September

Prediksi Jumlah Penjualan melalui Live Stream dan Affiliate di TikTok Shop dengan Machine Learning

Putri, Nabila Agustina Cahyani (Unknown)
Patrisiane, Viena (Unknown)



Article Info

Publish Date
30 Sep 2024

Abstract

Sales techniques have evolved rapidly from conventional methods to online methods often referred to as e-commerce. One of the types of e-commerce that exists in Indonesia is TikTok Shop, on TikToc Shop there are many sales supporting factors. The two sales supporting factors available on TikTok Shop are live stream and affiliate but there is no research to discuss the two factors simultaneously to the volume of sales. The aim of this study is to create a model to predict sales with live stream and affiliate factors on TikTok Shop. The method used in this research is by comparing the results of RMSE (Root Mean Squared Error) formed from the application of machine learning models multiple linear regression and random forest regression. The results of the study show that the best model based on RMSE for predicting sales with the live stream factor and the affiliate on TikTok shop is a multiple linear regression algorithm with RMSE(Root mean squared error) of 39.306882.

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Journal Info

Abbrev

JINRPL

Publisher

Subject

Computer Science & IT

Description

Journal of Informatics and Software Engineering accepts scientific articles in the focus of Informatics. The scope can be: Software Engineering, Information Systems, Artificial Intelligence, Computer Based Learning, Computer Networking and Data Communication, and ...