Metode K-Means Untuk Pemetaan Persebaran Usaha Mikro Kecil Dan Menengah
DOI:
https://doi.org/10.30646/tikomsin.v9i2.574Keywords:
K-Means Clustering, MSMEs, MappingAbstract
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.
Â
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.
Downloads
Published
Issue
Section
Citation Check
License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Â

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