Strategi Marketing Penerimaan Mahasiswa Baru Menggunakan Machine Learning dengan Teknik Clustering

Raditya Danar Dana, Cep Lukman Rohmat, Ade Rizki Rinaldi


The marketing activity of new student admissions is one of the efforts undertaken by a university to maintain its existence in order to remain known and gain interest from the wider community. From the results of observations made at the research location, marketing activities carried out so far are still carried out in the same way from year to year without distinguishing the characteristics of the target prospective registrants, so the marketing pattern undertaken is not necessarily effective for all prospective applicants who have different characteristics - different . Therefore, it is necessary to make an effort to target target applicants based on certain characteristics to facilitate the determination of strategies and marketing patterns for new student admissions. The aim of this research is to group students' spread data using Machine Learning Technology approach using Clustering technique. This research resulted in the grouping of registrants in the admission activities of new students divided into 3 cluster groups, namely cluster 1 by 11%, cluster 2 by 56% and cluster 3 by 33%.


Machine Learning; Clustering; K-Means

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Copyright: JPIT (Jurnal Informatika: Jurnal Pengembangan IT) p-ISSN: 2477-5126 (print), e-ISSN 2548-9356 (online) 

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Creative Commons License
JPIT (Jurnal Informatika: Jurnal Pengembangan IT) is licensed under a Creative Commons Attribution 4.0 International License.