Regional Segmentation Based on the Level of Digitalization of MSMEs in Indonesia
DOI:
https://doi.org/10.31098/ijeass.v5i2.3419Keywords:
K-Means Clustering, MSMEs, Digitalization.Abstract
Digitalization of Micro, Small, and Medium Enterprises (MSMEs) plays a vital role in enhancing national and international competitiveness. This study aims to conduct regional segmentation in 34 provinces in Indonesia based on several indicators of the level of digitalization of MSMEs. This research is a quantitative study and an analytical descriptive approach that uses analysis techniques (K-means cluster) to map the distribution of MSMEs in Indonesia. Data pre-processing by standardizing data (z-score) to overcome differences in units of measurement. The type of data used is secondary data from the Central Bureau of Statistics and the Indonesian Payment System Association. The study identifies three clusters with different characteristics. The first cluster, comprising West Java, Central Java, and East Java, shows advanced MSMEs digitalization. The second cluster consists of 30 provinces with a developing level of MSMEs digitization. The third cluster is occupied by Papua, which shows lagging MSMEs' digitalization. This research focuses on the uneven digitization of MSMEs by limiting the scope of research to 34 provinces in Indonesia, then does not include analysis of development in time series, financial aspects, or the impact of government policies on the development of MSMEs. The originality of this research lies in the use of 34 research objects in Indonesia in 2023 by applying non-hierarchical K-Means clustering analysis. The analysis in this study uses indicators including the distribution of MSMEs, the number of workers in the e-commerce sector, the number of e-commerce businesses, the level of QRIS adoption, and the use of social media.
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