Implementasi Metode DBSCAN Untuk Pengelompokkan Sebaran Wilayah Asal Mahasiswa Sebagai Strategi Promosi Kampus
DOI:
https://doi.org/10.64366/adajisr.v2i1.57Keywords:
Data Mining; Clustering; DBSCAN; Student; PromotionAbstract
Current database technology makes it possible to store huge amounts of accumulated data but this is where the data explosion problem arises, for example at the University. Budi Darma University Medan is still analyzing data manually to determine the promotion strategy plan of the geographic distribution of students. The distribution of students can be done by grouping student data based on the similarity of the characteristics of the data using the clustering method with the dbscan algorithm. Making data mining applications aims to make it easier to analyze student distribution groupings. The data used is data from the 2018 to 2019 batch of students. In this study the application was built using Rapid Miner. This technique can determine clusters of irregular data shapes and can handle noise effectively. This research focuses on the implementation of the DBSCAN method in the process of grouping the distribution of student areas from the university as a promotion strategy for the Budi Darma University campus in the future. It is hoped that the system will be built in accordance with the expectations of researchers, so that it can classify the distribution of student areas from as a Budi Darma University campus promotion strategy.
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