Abstract:
Many students at SMA Negeri 1 Lakbok often choose their study programs based
on the influence of friends or others, without carefully considering whether the
program aligns with their interests and talents. As a result, many students drop out
of school, feeling they've chosen the wrong program.
Therefore, the author conducted a data mining analysis using grade data of class
XII MIPA and IPS students. In the analysis, the author used Microsoft Excel and
SPSS tools. The method used is the K-Means Clustering method with 242 MIPA
student data and 92 IPS student data, 19 attributes and 10 MIPA clusters and 10
IPS clusters.
The number of MIPA Microsoft Excel calculations is 2 large, namely cluster 3 there
are 43 data recommended to enter mathematics education, cluster 7 there are 53
data recommended to enter chemical engineering. The number of calculations for
Microsoft Excel IPS is 2 large, namely cluster 3 contains 16 data recommended to
enter law, cluster 5 contains 12 data recommended to enter geography education.
And the number of calculations for SPSS MIPA is 2 large, namely cluster 1 contains
39 data recommended to enter informatics engineering, cluster 5 contains 40 data
recommended to enter Indonesian language education. The number of calculations
for SPSS IPS is 2 large, namely cluster 2 contains 14 data recommended to enter
accounting, cluster 7 contains 17 data recommended to enter Indonesian language
education.
