Penerapan Clustering Data untuk Pengelompokkan Usaha Mikro Kecil dan Menengah Berbasis Web
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Institusion
Politeknik Negeri Bengkalis
Author
Handayani, Dwi
Subject
458 Teknik Informatika
Datestamp
2022-09-12 10:33:50
Abstract :
Micro, Small and Medium Enterprises are business activities that are able to expand employment opportunities and provide broad economic services to the community, and can play a role in the process of equitable distribution and increase in people's income, encourage economic growth, and play a role in national stability. Based on the data collection process carried out by researchers to determine the development and number of MSMEs recorded on Bengkalis Island, researchers found problems with data collection and data storage of MSMEs at the SME Office of Bengkalis Regency such as incomplete data, all MSME data was only stored in one file and not separated by category of micro, small, and medium enterprises and there is no access to information on the location of MSMEs in Bengkalis Island. To overcome the problem of data grouping, data clustering can be done using the K-Means algorithm. Data clustering is carried out based on the criteria for MSME criteria, namely business capital, annual sales, and the number of workers. Based on the data clustering that has been done, there are cluster 1 with 45 businesses, cluster 2 with 4 businesses, and cluster 3 with 1 business. The results of the system testing carried out, the web has been able to do clustering and has provided information on MSMEs on Bengkalis Island.
Micro, Small and Medium Enterprises are business activities that are able to expand employment opportunities and provide broad economic services to the community, and can play a role in the process of equitable distribution and increase in people's income, encourage economic growth, and play a role in national stability. Based on the data collection process carried out by researchers to determine the development and number of MSMEs recorded on Bengkalis Island, researchers found problems with data collection and data storage of MSMEs at the SME Office of Bengkalis Regency such as incomplete data, all MSME data was only stored in one file and not separated by category of micro, small, and medium enterprises and there is no access to information on the location of MSMEs in Bengkalis Island. To overcome the problem of data grouping, data clustering can be done using the K-Means algorithm. Data clustering is carried out based on the criteria for MSME criteria, namely business capital, annual sales, and the number of workers. Based on the data clustering that has been done, there are cluster 1 with 45 businesses, cluster 2 with 4 businesses, and cluster 3 with 1 business. The results of the system testing carried out, the web has been able to do clustering and has provided information on MSMEs on Bengkalis Island.
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