PENGELOMPOKAN PRESTASI MATEMATIKA SISWA INDONESIA BERDASARKAN HASIL SURVEY TIMSS MENGGUNAKAN ANALISIS LOGISTIK KELAS LATEN
ABSTRACT: Conventional methods
of clustering become weak when meet measured objects with qualitative or
categorical data.Latent class logistic analysis can bean alternative method of
clustering to overcome this problem. This research is aim to see the
application of latent class logistic analysis to clusterthe measured objects
with qualitative and quantitative variable and at once to find out backgrounds
of the clusters. The objects in this research are 2171 eight grade students
from 133 schools in Indonesia. There are two resultsinthis research; first in
clustering and second in logistic analysis. In clustering, the students have
beenclustered into four ideal clusters,e.g.39.16 percent students were in
cluster1, 32.42 percent in cluster2, 21.46 percent in cluster3, and 6.97
percent in cluster4.Each cluster representsthe students with very low,
low,medium, andhigh ability in mathematics. In logistic analysis, overall, each
cluster has been explained well by covariatese.g. student’s interest, attitude,
aptitudeand motivation on mathematics, parent’ssocial-economic condition,
parent’s highest education level, teacher’s highest education level,teacher’s
major study of mathematics and educations,teacher’s perceptions on
schools,school’s facilities, etc.
Penulis: Riswan
Kode Jurnal: jppendidikandd131644
