Modeling MSME Growth: The Impact of Growth Stages, Mentoring, and Digital Literacy Using Decision Tree and Polytomous Logistic Regression

Yanto Setiawan; Aries Susanty; Daduk Merdika Mansur

doi:10.24167/sisforma.v12i2.14299

Modeling MSME Growth: The Impact of Growth Stages, Mentoring, and Digital Literacy Using Decision Tree and Polytomous Logistic Regression

Yanto Setiawan, Aries Susanty, Daduk Merdika Mansur

Abstract

Micro, Small, and Medium Enterprises (MSMEs) are vital to Indonesia's economy, yet their growth is often hampered by a lack of structured support and low digital adoption. This study models MSME growth by analyzing the impact of business growth stage, mentoring models, and digital literacy. Utilizing a dataset from PT Telkom Indonesia's CSR program, this research employs a two-stage quantitative method: first, a Decision Tree algorithm classifies MSMEs into five growth stages, and second, Polytomous Logistic Regression (PLR) analyzes the factors influencing their growth. The findings reveal that the mentoring model is the most dominant predictor of MSME growth, with the 'Hybrid' model proving most effective. Conversely, digital literacy did not show a significant direct impact when mentoring was included in the model, suggesting mentoring acts as a critical catalyst. This research provides an evidence-based framework for developing more effective, tiered mentoring programs tailored to the specific needs and developmental stage of MSMEs.

Keywords

MSME Growth; Mentoring Model; Digital Literacy; Business Stage; Decision Tree; Polytomous Logistic Regression

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DOI: https://doi.org/10.24167/sisforma.v12i2.14299