Modeling Academic Performance of The Students by using Partial Least Square
Marji1, Samingun Handoyo2, Endang W. Handamari3, Ni W. S. Wardhani4
1Marji*, Informatis Engineering department, University of Brawijaya, Malang, Indonesia.
2Samingun Handoyo, Statistics department, University of Brawijaya, Malang, Indonesia.
3Endang Wahyu Handamari, Mathematics department, University of Brawijaya, Malang, Indonesia.
4Ni Wayan Surya Wardhani, Statistics department, University of Brawijaya, Malang, Indonesia.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 5438-5443 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6835018520 /2020©BEIESP | DOI: 10.35940/ijrte.E6835.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This study aims to model the relationship between predictor variables consisting of learning motivation (LM), parents’ socioeconomic status (SS), and school environment (SE) which are all latent variables to academic achievement (AC) which are not latent variables. Modeling is done by the method of partial least square (PLS) which is expected to explore the various effects found in the inner model and also confirm the questionnaire items forming the latent variables. With a real level of 5%, almost all loading values on each latent variable are significant. Likewise, a simple linear relationship consisting of 5 models has a coefficient that has a significant effect. The influence of learning motivation (LM), parents’ socioeconomic status (SS), school environment (SE) on academic achievement are 0.270, 0.249, and 0.320, respectively. while learning motivation (LM), socioeconomic status of parents (SS) contributing to academic achievement (AC) were 17.7% and 3.13%, respectively..
Keywords: Academic performance, indirect effect, latent variable, modeling real problem.
Scope of the Article: Smart learning and innovative education systems