JASDS: Journal of Applied Statistics and Data Science
Vol. 1 No. 1 (2024): Journal of Applied Statistics and Data Science

Development of Seemingly Unrelated Regression Analysis with Dummy Variables: Modeling the Relationship of Student Learning Outcome Indicators




Article Info

Publish Date
28 Mar 2024

Abstract

This research aims to develop a seemingly unrelated regression model with dummy variables to determine the relationship between factors that influence student learning outcomes in each subject which includes Religious Education, Citizenship, Indonesian, English, Mathematics, Sciences, Social Science, Cultural Arts, Physical Education and Crafts. This research is applied sciences using primary data obtained through a list of questions (questionnaire) given to class IX students at SMP Negeri 42 Batam. The predictor variables of this research include students' creativity, motivation, interests, talents, support from parents, friends and school where interests are the intercept dummy for this research. The results of the research show that there is a positive relationship between interest and the value of each subject and parental support in 9 subjects, but there is a negative relationship between school support in 8 subjects. Creativity and motivation have no relationship in every subject. The regression model obtained was good because 99.6% of the response variables could be explained by the predictor variables. It is hoped that this research will be used as evaluation material for students, parents and schools to improve learning outcomes where class IX students will of course pursue higher education the following year.

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Journal Info

Abbrev

jasds

Publisher

Subject

Computer Science & IT Mathematics

Description

JASDS : Journal of Applied Statistics and Data Science (e-ISSN: 3048-4391) is a journal managed by Universitas Brawijaya , Malang, Indonesia, and associated with FORSTAT (Forum Pendidikan Tinggi Statistika) which is published twice a year (in March and October). The objectives of Journal of Applied ...