Penerapan K-Means Clustering Dalam Menentukan Banyaknya Desa/Kelurahan Menurut Keberadaan dan Jenis Industri Kecil dan Mikro (Desa)
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Fira Fania
*
STIKOM Tunas Bangsa, Pematang Siantar,
Indonesia
- Agus Perdana Windarto STIKOM Tunas Bangsa, Pematang Siantar, Indonesia
- Dedy Hartama STIKOM Tunas Bangsa, Pematang Siantar, Indonesia (*) Corresponding Author
Abstract
Processing Industry is an economic activity that carries out activities to change a basic item mechanically, chemically, or by hand so that it becomes finished / semi-finished goods, and or goods of less value to goods of higher value, and which are closer to the end user. This study aims to model the grouping in determining the Number of Villages / Villages According to the Existence and Types of Small and Micro Industries (Villages). This research is a reference, especially for the government, so that the potential for employment in this industry group can continue to be developed and optimized. Government contributions can be realized through the creation of stable social, economic and political conditions and through the policy of determining the direction of business development of Micro and Small Industries. The data from this study were taken from a government statistical data provider website, BPS (Statistics Indonesia) www.bps.go .id. This research uses the K-Mens method and is tested with RapidMiner software to create 3 clusters, namely high, medium and low level clusters and see what the contents of the cluster are. From the research results obtained by high cluster data centroids namely ((2151.79), ( 1494.34), (1135.76), moderate clusters ((406.64), (525.06), (616,218), and low clusters ((455,361), (345,523), (1074.09), (176,434), (1410,34), (243,749), (295,151), (463,266), (5868,13), (9344.07), (170,925), (8818,85), (1031,65), (433,61), (5985,505), (1630,75), (367,928), (119,082), (560,907), (172,333), (545,342), (226,174), (776,643), (1880,857), (172,333), (545,342), (226,174), (776,643), (1880,853), (1880,853), (18,80,853), (1880,853), (1880,853), (1880,853), (1880,853), (1880,853) ), (1482.39), (115,573), (232,734), (187.04), (142,884), (455,674), (441,934) With this analysis expected to be input and information for the government of each region to pay more attention to regions micro / small industrial areas occupying low clushter (C1) positions in order to improve industrial quality in the region.
References
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