Penerapan K-Means Clustering Pada Data Mahasiswa Fakultas Interdisiplin Program Studi D4 Destinasi Pariwisata Untuk Menentukan Strategi Promosi

Abstract

The research was conducted to see the trend of supply of students studying at the Interdisciplinary Faculty, Tourism Destination D4 Study Program. The algorithm used in the student supply process is K-means. Data processing with the K-means algorithm helps extract information and knowledge from student data in the Interdisciplinary Faculty, D4 Tourism Destination Study Program. By using data mining, stakeholders in the Interdisciplinary Faculty, D4 Tourism Destination Study Program, can take strategic steps in the screening process in provinces that are indicated to supply students. The K-means algorithm facilitates the process of data analysis and grouping of student data for 4 years. The purpose of this research is to provide an accurate and strategic picture of the provinces that can have a significant impact on the supply of students each year. The results showed that the largest supply of students came from Central Java and the smallest from Bangka Belitung, West Sulawesi, Banten, East Kalimantan, West Papua, Bengkulu and Riau, so promotion strategies need to be improved in areas with the smallest student supply.