Implementasi Metode K-Means Dalam Klasifikasi Desa/Kelurahan Menurut Jenis Industri Kecil Mikro
DOI:
https://doi.org/10.47065/jimat.v2i1.152Keywords:
Data Mining; K-Means Algorithm; Grouping; Small and Micro IndustriesAbstract
The Ministry of Industry noted that the number of small and medium industries in Indonesia reached 44 million. But unfortunately 99% of all small industries have problems and difficulties in developing their businesses. The problem that is often faced in Indonesia is the limited ability of digital marketing. Unstable production and others. In order to help/support small and micro businesses, a grouping is carried out in the Pematangsiantar sub-district that has small/micro businesses according to the type of business using the K-Means method. The research data used were obtained from BPS and grouped into 2 high and low groups. By implementing the k-means method in the rapidminer application, it is possible to produce a decision tree based on the previous learning data set of small and micro-medium industries using criteria intended to produce relevant and accurate results of small and medium-sized industrial business classification
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