Penerapan Algoritma K-Means Dalam Pengelompokan Pekerja Tetap Perusahaan Konstruksi Menurut Provinsi

Khairwa Bakhsar(1*), Widodo Saputra(2), Heru Satria Tambunan(3),

(1) STIKOM Tunas Bangsa, Pematangsiantar, Medan – Indonesia
(2) AMIK Tunas Bangsa, Pematangsiantar, Medan – Indonesia
(3) STIKOM Tunas Bangsa, Pematangsiantar, Medan – Indonesia
(*) Corresponding Author

Abstract


A construction company is one of the economic sector businesses that deal with planning and supervision of construction activities to form a building. Permanent workers, namely workers who have a work agreement with the employer for a period of time not based on a decision letter. Based on data obtained from the official Government website, which is located at https://www.bps.go.id/, which displays several numbers ranging from 2010 to 2018 according to provinces in Indonesia. For this reason, the data will be processed by clustering in 2 clusters, namely the highest and lowest, using the Data Mining method with the K-Means Algorithm. In this research technique, the data will be grouped based on the province's name that has the number of permanent construction company workers from 2010 to 2018. The Data Mining method is used to facilitate data grouping of the number of construction company permanent workers according to provinces in Indonesia. The decision-based results were based on the number of permanent workers in construction companies by province with the highest 1 province, namely DKI Jakarta and 33 other provinces, including the lowest level. It is hoped that this research can be an input to the government, provinces that have become more concerned with construction companies based on the clusters that have been carried out.

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DOI: https://doi.org/10.30645/kesatria.v1i4.40

DOI (PDF): https://doi.org/10.30645/kesatria.v1i4.40.g40

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