Clustering Digital Transformation of Small and Medium Enterprises (SMEs) Using Fuzzy K-means Method
Riansyah A., Qomaruddin M., Indriastuti M., Sagaf M.
Abstract
Digital transformation of Small and Medium Enterprises (SMEs) is an effort to advance the competitiveness and productivity of SMEs through grouping based on specific criteria. One of the clustering techniques that can be used is Fuzzy K-means. This method allows for a more flexible grouping of SMEs, bearing in mind that each SME can have different relationships in each group. This study aims to apply the Fuzzy K-means method in an information system for SME clustering based on the variables Type of SME product, Dynamic Capabilities, Workforce Transformation, and SME Performance. The results of this study indicate that there are three groups of SMEs, namely large, medium and small enterprises. This research can provide critical information for the government and SME support institutions as a decision support system in providing more targeted assistance and support for each SME group. In addition, the results of this study can also help SMEs to increase their competitiveness and productivity through increasing access to markets, technology, and capital following the characteristics of the SME group.