Metode K-Means Untuk Pemetaan Persebaran Usaha Mikro Kecil Dan Menengah

Dwi Remawati, Dicky Jordan Aji Putra, Tri Irawati

Abstract


Developments in the current era of globalization are very dependent on the economic sector which is the benchmark of success carried out by the government. The role of the community in national development in the economic field is the existence of Micro, Small and Medium Enterprises (MSMEs). To increase the role of MSMEs as a benchmark for the success of the economic sector, there must be support from the government, such as assistance for business owners with limited costs. The purpose of this study is to determine community business groups as a measure of the level of business, making it easier for the government to provide assistance. The K-Means Clustering method is a method used for grouping business levels based on the income that exists in today's society. The result of this research is a website-based business-level grouping system used by the Cooperatives and SMEs Office by grouping them into micro, small and medium-sized businesses based on income/assets.

 


Keywords


K-Means Clustering, MSMEs, Mapping

Full Text:

PDF

References


G. Gustientiedina, M. H. Adiya, and Y. Desnelita, “Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan,” J. Nas. Teknol. dan Sist. Inf., vol. 5, no. 1, pp. 17–24, 2019.

B. M. Metisen and H. L. Sari, “Analisis clustering menggunakan metode K-Means dalam pengelompokkan penjualan produk pada Swalayan Fadhila,” J. Media Infotama, vol. 11, no. 2, pp. 110–118, 2015.

mohamad jajuli nurul rohmawati, sofi defiyanti, “Implementasi Algoritma K-Means Dalam Pengklasteran Mahasiswa Pelamar Beasiswa,” Jitter 2015, vol. I, no. 2, pp. 62–68, 2015.

W. Safira Azis and dan Dedy Atmajaya, “Pengelompokan Minat Baca Mahasiswa Menggunakan Metode K-Means,” Ilk. J. Ilm., vol. 8, no. 2, pp. 89–94, 2016.

R. A. Asroni, “Penerapan Metode K-Means Untuk Clustering Mahasiswa Berdasarkan Nilai Akademik Dengan Weka Interface Studi Kasus Pada Jurusan Teknik Informatika UMM Magelang,” Ilm. Semesta Tek., vol. 18, no. 1, pp. 76–82, 2015.

N. A. Widiastuti and N. A. Azizah Widiastuti, “Teknologi Geolocation Berbasis Android dengan Metode K-Means untuk Pemetaan UMKM di Kabupaten Jepara,” J. Sist. Inf. Bisnis, vol. 8, no. 2, p. 218, 2018.

P. Puntoriza and C. Fibriani, “Analisis Persebaran UMKM Kota Malang Menggunakan Cluster K-means,” JOINS (Journal Inf. Syst., vol. 5, no. 1, pp. 86–94, 2020.

W. Aristika and W. J. Hartono, “Penerapan Clustering K-Means untuk Menentukan Pengaruh Media Sosial Facebook terhadap Usaha Mikro, Kecil dan Menengah (UMKM) di Kecamatan Pekanbaru Kota,” J. Ilmu Komput. dan Bisnis, vol. 11, no. 1, pp. 2389–2395, 2020.




DOI: http://dx.doi.org/10.30646/tikomsin.v9i2.574

Refbacks

  • There are currently no refbacks.


Editorial Office :
TIKomSiN : Jurnal Teknologi Informasi dan Komunikasi Sinar Nusantara
Published by STMIK Sinar Nusantara Surakarta
Address KH Samanhudi 84 - 86 Street, Laweyan Surakarta, Central Java, Indonesia
Postal Code: 57142, Phone & Fax: +62 271 716 500
Website: https://p3m.sinus.ac.id/jurnal/index.php/TIKomSiN
Email: tikomsin @ sinus.ac.id

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Stats of tikomsin