Analisa Nilai Lamda Model Jarak Minkowsky Untuk Penentuan Jurusan SMA (Studi Kasus di SMA Negeri 2 Tualang)
Abstract: SMA Negeri 2 (SMAN
2) is located in Tualang. So far the data report student majors only stored in
a database as a final report. Data from the report of the majors could be used
as guidelines to determine the students' decision majors for the following
year. To take advantage of the data stored in that particular database, we can
use data mining disciplines. The method used to make the determination of
students majoring done by using Nearest K-Nearest Neighbor (K-NN) algorithm. On
the other hand, the method for calculating the distance between the data used
models Minkowsky distance with a value of lambda (λ) as a parameter. Lambda
values that were analyzed were lambda 1, 2 and 3. Lambda with the value of 1
can generate increasing accuracy in the 11th experiment or with a large amount
of data equal to 276 data. Lambda 2 will produce increasing accuracy by the
16th experiment or with the number of training data equal to 356 data while
lambda 3 can also produce accuracy continuously increasing by the 11th
experiement or with the amount of training data equal to 276 data. The accuracy
of the lambda value of 1 is better than lambda 2 and lambda 3. This was proven
in 25 experiments at lambda 1 which produces the highest accuracy value for 20
times.
Penulis: Khairul Umam Syaliman
bin Lukman, Ause Labellapansa
Kode Jurnal: jptinformatikadd150359
