Strategi Marketing Penerimaan Mahasiswa Baru Menggunakan Machine Learning dengan Teknik Clustering

Raditya Danar Dana, Cep Lukman Rohmat, A. Rinaldi
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引用次数: 3

Abstract

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%.
新生入学营销活动是大学维持其存在的努力之一,目的是保持知名度并获得更广泛社区的兴趣。从研究地点的观察结果来看,迄今为止开展的营销活动每年都以同样的方式进行,没有区分目标潜在注册者的特征,因此所采取的营销模式不一定对所有具有不同特征的潜在申请人都有效。因此,有必要根据某些特点,努力瞄准目标申请人,以便于确定新生招生的策略和营销模式。本研究的目的是使用聚类技术的机器学习技术方法对学生的传播数据进行分组。本研究将新生入学活动的注册人分组分为3个集群组,即集群1占11%,集群2占56%,集群3占33%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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