Strategi Promosi Menjaring Mahasiswa Baru Berdasakan Segmentasi Data PPMB Menggunakan K-Means
DOI:
https://doi.org/10.58776/jriti.v1i1.57Kata Kunci:
Mahasiswa Baru, K-Means, Clustering, strategi, promosiAbstrak
The number of universities that are spread out causes promotional strategies to greatly affect the number of new student admissions at any university including Bhayangkara University of Greater Jakarta. It is necessary to have the right strategy to be able to shape the characteristics and improve the quality of education at the University by understanding the right data segmentation to match the promotion target. This effort was carried out with the aim of determining a promotion strategy based on the location of residence, school origin, and parents' salary so that promotional activities run effectively every year. The data used in this study are data from the results of the new student admission process of Bhayangkara University Jakarta Raya in 2018-2022 which will then be processed. The data that has been managed will be processed through the KDD (Knowledge Discovery in Database) analysis technique [1] with 5 stages, namely selection, pre-processing, transformation, data mining, and evaluation, so as to produce a data mining analysis by considering the theory of the K-Means clustering algorithm as a research method.
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