Utilization of Data Mining in the Processing of Average Values of High School Level National Examination at the Department of Natural Sciences in Indonesia

Lukman Nasution, Siti Choiriyah, Abdul Rahmat, HeldyVanni Alam, Salam

The Computer Standards National Examination (abbreviated as UNBK) computer standard is a phenomenon of technological progress that has a big impact and impact on all aspects of life such as the world of education in Indonesia which is demanded to always develop every year so that Indonesian people get better quality education. The purpose of this research is to apply data mining techniques in analyzing the processing of the national standardized high school-level computerized national exam score in the Department of Natural Sciences in Indonesia. The data used is the data of the Ministry of Education and Culture processed by the Central Statistics Agency. The attribute used is the average UNBK grade at the high school level majoring in Natural Sciences by province 2018/2019 academic year consisting of 35 provinces. The method used is KMedoids which is part of clustering. By using Davies-Bouldin Index (DBI) obtained 2 cluster labels namely C1: high cluster and C2: low cluster with the best DBI is 0,427. The results of the study stated that only 14,3% or 5 provinces were included in the high cluster (C1) namely: Bali, DKI Jakarta, Central Java, Riau islands and Yogyakarta. While 85,7% or 30 other provinces are included in the lower cluster (C2). For the final centroid value used for each cluster are C1 = 65,35 and C2 = 47,93. It is expected that the results of the study can provide information to the government that some provinces in western, central and eastern Indonesia are still in the lowest position that has an impact on the quality of education in Indonesia.The analysis of each clustering experiment is presented in this paper.

Volume 12 | Issue 6

Pages: 2090-2096

DOI: 10.5373/JARDCS/V12I6/S20201170