Strategi Marketing Penerimaan Mahasiswa Baru Menggunakan Machine Learning dengan Teknik Clustering

Jurnal Informatika: Jurnal Pengembangan IT

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Field Value
 
Title Strategi Marketing Penerimaan Mahasiswa Baru Menggunakan Machine Learning dengan Teknik Clustering
 
Creator Dana, Raditya Danar; STMIK IKMI Cirebon
Rohmat, Cep Lukman; STMIK IKMI Cirebon
Rinaldi, Ade Rizki; STMIK IKMI Cirebon
 
Subject
Machine Learning; Clustering; K-Means
 
Description 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%.
 
Publisher Politeknik Harapan Bersama
 
Contributor
 
Date 2019-12-19
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier http://ejournal.poltektegal.ac.id/index.php/informatika/article/view/1879
10.30591/jpit.v4i2-2.1879
 
Source Jurnal Informatika: Jurnal Pengembangan IT; Vol 4, No 2-2 (2019): Special Issue on Seminar Nasional - Inovasi Dalam Teknologi Informasi & Teknologi Pembelajaran; 201-204
2548-9356
2477-5126
10.30591/jpit.v4i2-2
 
Language eng
 
Relation http://ejournal.poltektegal.ac.id/index.php/informatika/article/view/1879/pdf_52
10.30591/jpit.v4i2-2.1879.g1120
 
Rights Copyright (c) 2020 Jurnal Informatika: Jurnal Pengembangan IT
http://creativecommons.org/licenses/by/4.0
 

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