Instagram Marketing for Brand Awareness in Certification and Training MSMEs: Insights from Social Media Analytics - Dian Addinna; Gilang Garnadi Suryadi; Yosep Hernawan; Edi Suryadi; Asep Miftahuddin; Rizqiana Arifatul Husna (Daengku: Journal of Humanities and Social Sciences Innovation, 2026)
Early-stage micro, small, and medium enterprises (MSMEs) in the certification and training sector often struggle to build brand awareness on Instagram, where success depends heavily on trust, competence, and credibility. Most prior research has measured the effect of social media marketing through surveys rather than producing a directly applicable, data-driven model, and the certification services sector remains underexplored. This study addresses that gap by analysing Instagram discourse on professional certification and formulating an evidence-based Instagram marketing model. Using a social media analytics approach, 2,000 posts were collected through the SocialX application with the hashtag #sertifikasiprofesi and examined through five procedures: word cloud analysis, text network analysis, emotion analysis using an Indonesian RoBERTa model, sentiment network analysis, and BERTopic modelling. The findings show that the discourse is anchored in competency- and institution-oriented language (notably recognised schemes such as BNSP and LSP), framed around tangible career benefits, expressed through predominantly neutral-to-positive sentiment, and circulated within a sparse, broadcast-oriented network (288 nodes, 240 edges, density 0.6%) dominated by a few central institutional accounts. Based on these findings, this study proposes a marketing model that emphasises recognised credentials, concrete career outcomes, distinctive storytelling, cross-platform integration, and collaboration with influential accounts. The model is analytically derived; its implementation and evaluation are recommended for future research.