Optimalisasi Penyaluran Bantuan Pemerintah Untuk UMKM Menggunakan Metode Fuzzy C-Means

Optimalisasi Penyaluran Bantuan Pemerintah Untuk UMKM Menggunakan Metode Fuzzy C-Means

Clustering, Data Mining, Fuzzy C-Means, MSMEs

ndonesian MSMEs were very seriously affected by the Covid-19 pandemic, which caused the Indonesian economy hasexperienced deceleration. The Indonesian government has taken several steps to keep economic activity running, such as direct cash assistance for micro-scale businesses but is havingproblems in obtaining real data so that assistance is not on target, the clustering method using Fuzzy C-Means (FCM) is used for grouping MSME data. FCM allows the data to be a member of all clusters in which each cluster has a membership degree value of 0-1. The data used is from the website of the Sleman Regency Cooperatives and SME Service.FCM classifies MSME data based on the attributes of revenue, assets and number of workers. This research resulted in grouping MSME data into 3 priority levels for MSMEs in obtaining assistance, namely high priority, medium priority, and low priority. The results of this study show that the number of MSMEs with high priority is 23,023 MSMEs, medium priority is 9,774 MSMEs and low priority is 3,159 MSMEs. The validation test of the FCM method uses the Partition Coefficient Index (PCI) which has a value of 0.826 which means that value good because it is close to 1.

Anggara Cahya Putra1, Kristoko Dwi Hartomo

https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23

Universitas Kristen Satya Wacana

20 juni 2021

Fajar bagus W

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Indonesia

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