Determining The Amount Of Tuition Fees For New Budidarma Students With Data Mining Using The K-Means Clustering Algorithm
Keywords:
PTS, PTN, UKT, Dynamicsome, Clustering, K-Means.Abstract
One of the variables that determines the quality of education in higher education is the amount of fixed tuition fees that must be paid by students to the academic community, which must be in sync with their parents' income. Although the quality of education can be measured from the consistency of supervision, compliance of teachers and students with the System Operating Procedure (SOP), and the availability of complete teaching and learning infrastructure. In private universities, to determine fixed tuition fees, one method that can be used is to find patterns or information on fixed tuition fees at other private universities in the same area (region) by drawing from a large database, which is data mining. It is very important for a private university to know the patterns of prospective students from the data in the database owned by a campus. This technique is the K-Means Clustering Algorithm. The results of the discussion will describe the amount of affordable tuition fees that will be provided with a list with variations based on the study program chosen by prospective students, where each department is distinguished by the completeness of administration and infrastructure in the study program.
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