Please use this identifier to cite or link to this item:
https://repository.uksw.edu//handle/123456789/26730
Title: | Analisis Persebaran UMKM Kota Malang Menggunakan Cluster K-Means |
Authors: | Puntoriza |
Keywords: | K-Means Cluster;Kota Malang;UMKM;Weka |
Issue Date: | 14-Jul-2020 |
Abstract: | UMKM (Usaha Mikro Kecil dan Menengah) merupakan usaha produktif yang telah terbukti memberikan lapangan kerja dan menjadi penggerak roda perekonomian di Indonesia. Kota Malang dianggap memiliki potensi besar di sektor UMKM. Di sisi lain, UMKM juga menghadapi berbagai masalah, seperti keterbatasan modal kerja, kurangnya pembinaan terhadap sumber daya manusia, dan lain sebagainya. Pengelompokan UMKM di Kota Malang dapat memudahkan pemerintah terkait dalam hal memilih peminjaman modal, menentukan potensi usaha dan menetapkan strategi pemasaran. Pada penelitian ini, pengelompokan UMKM di Kota Malang dilakukan dengan algoritma K-means cluster analysis. Hasil yang diperoleh adalah terbentuk 3 cluster, di mana algoritma K-means mengelompokkan kecamatan Blimbing ke cluster 1, kecamatan Klojen ke cluster 2, kecamatan Sukun ke cluster 3, Kecamatan Kedung Kandang ke cluster 3, dan Kecamatan Lowokwaru ke cluster 3. MSME (Micro, Small and Medium Enterprises) is a productive business that has been provent to provide employment and drive economic development in Indonesia. Malang is consider to have great potential in the MSME sector. On the other hand, MSMEs also face various problems, such as limited working capital, lack of workforce skills, and so forth. The grouping of MSMEs in Malang can facilitate the government in terms of choosing capital loans, determining business potential and determining marketing strategies. In this study, the grouping of MSMEs in Malang was done using the K-means cluster analysis algorithm. The results obtained are formed 3 clusters, where the K-means algorithm groups Blimbing sub-district into cluster 1, Klojen sub-district to cluster 2, Sukun sub-district to cluster 3, Kedung Kandang sub-district to cluster 3, and Lowokwaru sub-district to cluster 3. |
URI: | https://repository.uksw.edu/handle/123456789/26730 |
Appears in Collections: | T1 - Information Systems |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
T1_682013018_Abstract.pdf | Abstract | 133.49 kB | Adobe PDF | View/Open |
T1_682013018_Full text.pdf Until 2999-01-01 | Full text | 1.68 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.