PENERAPAN ALGORITMA K-MEANS CLUSTERING UNTUK MENENTUKAN STRATEGI PROMOSI UNIVERSITAS ISLAM NEGERI SUNAN KALIJAGA YOGYAKARTA

BAYU RESI INDRAWAN, NIM. 12651052 (2018) PENERAPAN ALGORITMA K-MEANS CLUSTERING UNTUK MENENTUKAN STRATEGI PROMOSI UNIVERSITAS ISLAM NEGERI SUNAN KALIJAGA YOGYAKARTA. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

New admissions process of UIN Yogyakarta University students generate data that are highly abundant in the form of student profile data. Based on it some hidden information could be known by doing data processing using that‟s profile‟sdataand also obtaining useful information for university. Information that we get could be contribute for university as a consideration to decide new admissions promotionin the next year. This research aims to classify student data‟s into a cluster by utilizing Data Mining processusing clustering techniques. The algorithm used for the cluster techniques is K-Means algorithm. K-Means is one method of non-hierarchical clustering of data that can group student data into several clusters based on the similarity of the data, so the data of students who have similar characteristics are grouped into one cluster and that have different characteristics grouped in another cluster. Atributes that used in this study is student‟s country,student‟s high school, and GPA for two semesterswith a value above 2,75. Cluster that formed after K-Means Algorithm process is three cluster with the first cluster amounted to 508 student data, second cluster amounted to 139 student data, and the third cluster amounted to 62` student data. Cluster with the highest average GPA is the first cluster. The results of this research are usedfor a making decision to determine promotion strategy based on clusters formed.

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