Machine Learning Adoption Model for SME E-Commerce Enhancement

Sales via e-commerce have become a must for companies, along with the increasing use of information technology by sellers and buyers to support sales transactions. Almost all retail companies use e-commerce to support the sale of their products, even many companies that only serve online sales via e-commerce. SMEs are businesses that use e-commerce to support their sales. However, the sale of SMEs via e-commerce is not in accordance with the specified sales target, so the adoption of e-commerce is not effective for SMEs. Machine learning is a technology that can help SMEs increase the effectiveness of selling via e-commerce. With machine learning, SMEs can increase the effectiveness of sales via e-commerce with the results of feature recommendations on SME e-commerce. Therefore, the goal of this research is to create a model of adaptation using machine learning for improving small and medium-sized enterprise (SME) online sales. A literature analysis is used as the basis for this study to determine the issues plaguing small and medium-sized enterprises (SMEs) and builds a machine learning adoption model for e-commerce based on previous research.