Enactment of Opinion Mining for Medium and Small Medium Enterprises in the Face of Digital Marketing Era

¹ Department of Digital Business, Lancang Kuning University, Pekanbaru 28261, Indonesia.
² Department of Informatics Engineering, Lancang Kuning University, Pekanbaru 28261 Indonesia.
³ Department of Information Systems, Lancang Kuning University, Pekanbaru 28261, Indonesia
⁴ Department of Indonesian Literature, Lancang Kuning University, Pekanbaru 28261, Indonesia.

^* Corresponding author: walhidayat@unilak.ac.id

Abstract

This research article aims to investigate the sentiment of Medium and Small Medium Enterprises (MSMEs) towards digital marketing using machine learning algorithms. In the growing digital era, digital marketing has become a key element in the marketing strategy of MSMEs. While digital marketing is pivotal for MSME growth in the digital era, there is a notable gap in understanding MSMEs’ attitudes and adoption challenges. This research uses sentiment analysis methods with machine learning algorithms to analyze data from various sources, including social media, online reviews, and surveys. The results of this study are expected to provide deep insights into how MSME players perceive and view digital marketing, whether positively or negatively, as well as what factors influence their views. The findings can serve as an important foundation for the development of more effective and sustainable marketing strategies for MSMEs in the face of challenges and opportunities in the digital era. The application of machine learning for nuanced sentiment analysis in MSME digital marketing offers valuable insights to refine marketing strategies and foster sustainable digital growth for small businesses.