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Abstract

In rural areas of Indonesia, micro, small, and medium enterprises (MSMEs) are often isolated; however, they have been proven to play an important role as the economic backbone of millions of communities. In fact, the sluggish development of MSMEs in Indonesia become a severe problem for the community welfare. The government continues to strive for the welfare of the local communities, one of which is by supporting the existing MSMEs. However, the provision of government assistance may not be optimal for the incorrect target of the MSMEs. This study informs the government and other related parties regarding subdistrict groups whose MSMEs are considered to be their target. The k-affinity propagation method was used to find a set of representative examples, called exemplars, that best summarize the data. The result shows that sub-districts clusters based on general welfare in five commodities. K-affinity propagation algorithm clusters vary by commodity. Data fluctuation from each commodity’s three factors causes this. From this research, it can be determined which subdistricts have the most or least prosperous MSMEs in each of the five commodities analyzed.

Keywords

MSMEs K-affinity propagation Commodity

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How to Cite
Tarisya Qurrota A’yuni, Baiq Nina Febriati, Lazuardy Ilham Effendie, Muhammad Muhajir, & Yotenka , R. . (2023). MSME Sales Clustering Based on Business Aid Distribution Priority Using K-Affinity Propagation. Enthusiastic : International Journal of Applied Statistics and Data Science, 3(1), 111–124. https://doi.org/10.20885/enthusiastic.vol3.iss1.art10
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