PENERAPAN METODE CHAID UNTUK MENGKLASIFIKASIKAN FAKTOR-FAKTOR YANG MEMPENGARUHI PRESTASI AKADEMIK MAHASISWA JURUSAN MATEMATIKA TAHUN MASUK 2016 FMIPA UNP

Gina Merdekawati, Nonong Amalita

Abstract


The mathematics department of UNP is one of the most popular majors every year. But the capacity for admission of new students is limited. By limiting the capacity for each department, it causes a strict selection so that students who are accepted are chosen students who have met the specified acceptance criteria. However, students are still constrained in the learning process. This has an impact on the results of studies achieved by students not as expected. Factors affecting academic achievement are
gender, national examination average, school origin, entry paths, choice of majors, scholarships, colleges while working, active organizations, tutoring for courses. The purpose of this research is to find out the variables that have significant influence, classification, and characteristics that are formed from the academic achievements of the 2016 Mathematics Department Students of the Faculty of Mathematics and Natural Sciences.CHAID analysis is one of the categorical data analysis which aims to determine the classification / grouping of any factors that affect the academic achievement of students majoring in mathematics at the Faculty of Mathematics and Natural Sciences UNP. The data in this study are primary data derived from filling out the questionnaire by students majoring in mathematics in 2016 FMIPA UNP. The sampling technique is total sampling.The results of the study using CHAID analysis produced 3 variables that significantly influence the academic achievements of the
Department of Mathematics in 2016 FMIPA UNP, namely scholarships, tutoring for courses, and the origin of schools consisting of 5 classifications with the characteristics / characteristics of students who are having high academic achievements with a minimum GPA of 3 are students who receive scholarships and take tutoring for college subjects.
Keywords: Labor Participation, Probit regression analysis

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