Application of Data Mining to Determine Promotion Strategy Using Algorithm Clustering at SMK Yadika 1

Abstract

The Promotion Strategy is very important to achieve the desired target, in determining the School Promotion Strategy for the results of new student admissions and in recommending the right promotion that can be used to overcome the problems faced by SMK Yadika which experienced a decrease in the number of new students from the 2017/2018 class entering 267 new student, then experiencing difficulties in determining promotion strategies, and promotion decisions taken by the school are sometimes not right on target, even though the position of SMK Yadika has a very strategic environment or place that can produce and get a lot of students. This study aims to apply the K-Means algorithm in the Promotion Strategy grouping which produces seven clusters based on the K Optimal Davies Bouldin Index so that it can be used to determine the right promotion strategy and develop an information system prototype to assist schools in compiling and deciding the right promotion. The results of this research, schools can carry out promotions based on the origin of the student's school, promotions based on the field of study of interest, promotions based on the study program expertise, promotions based on competency skills, and promotions based on the district where the student lives or domicile. With the results of clustering using the K-Means methodology, Cluster 1 (17.71%), cluster 2 (32.67%), cluster 3 (10.43%), cluster 4 (5.7%), cluster 5 (4.55 %), cluster 6 (3.34%), and cluster 7 (25.78%).

Keywords

• data mining, promotion strategy, clustering, davies bouldin index, crips-dm