Segmenting perceptions of social media's impact on MSMEs using K-means

The rapid growth of social media usage has significantly influenced the marketing and development strategies of Micro, Small, and Medium Enterprises (MSMEs). However, there remains a limited understanding of how various users perceive the role of social media in supporting MSME growth. This study aims to segment user perceptions regarding the impact of social media on MSMEs, utilizing the K-Means Clustering method. The research novelty lies in combining perceptual analysis with an unsupervised machine learning technique to discover hidden patterns in public responses. Data were collected through a questionnaire distributed to MSME actors and users of MSME products across Indonesia. The questionnaire includes statements related to the accessibility, promotional effectiveness, and trust-building capability of social media. The clustering results categorize respondents into several perception groups—ranging from highly positive to neutral or skeptical, providing valuable insights for stakeholders and digital marketing strategists in targeting communication and support for MSMEs. This approach offers a data-driven strategy to optimize MSME empowerment through the appropriate use of digital platforms.