Quantifying the Causal Impact of Employment Trends on Academic Performance Using Time-Series and Public Interest Data in Indonesia

This study quantifies the causal impact of employment trends on academic performance using a hybrid model of survey data and time-series public interest data from Google Trends in Indonesia. Employing Granger causality and regression analysis, the research investigates eight determinants of GPA and their relationship to labor indicators. A purposive sample of 40 respondents and secondary data from 2011–2019 were analyzed. Granger tests reveal significant one-way causality from employment to GPA indicators, particularly in parental monitoring (F = 7.06; p < 0.05) and learning motivation (F = 9.68; p < 0.05). Regression analysis supports these findings with R² values above 0.50. Results highlight the potential of integrating behavioral data into educational analytics. This research contributes methodological innovation by incorporating public interest data to explain academic outcomes, with implications for predictive modeling in education policy and planning.

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Publication Details

Journal
Advance Sustainable Science Engineering and Technology
Published
2025-08-28
DOI
https://doi.org/10.26877/d8ph2h66
Primary Topic
Islamic Finance and Banking Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Quantifying the Causal Impact of Employment Trends on Academic Performance Using Time-Series and Public Interest Data in Indonesia

Arif Ridho Lubis, Muharman Lubis, Alif Noorachmad Muttaqin, Tomi Mulhartono
Advance Sustainable Science Engineering and Technology
Islamic Finance and Banking Studies
article

Quantifying the Causal Impact of Employment Trends on Academic Performance Using Time-Series and Public Interest Data in Indonesia

Arif Ridho Lubis, Muharman Lubis, Alif Noorachmad Muttaqin, Tomi Mulhartono
article en

Abstract

This study quantifies the causal impact of employment trends on academic performance using a hybrid model of survey data and time-series public interest data from Google Trends in Indonesia. Employing Granger causality and regression analysis, the research investigates eight determinants of GPA and their relationship to labor indicators. A purposive sample of 40 respondents and secondary data from 2011–2019 were analyzed. Granger tests reveal significant one-way causality from employment to GPA indicators, particularly in parental monitoring (F = 7.06; p < 0.05) and learning motivation (F = 9.68; p < 0.05). Regression analysis supports these findings with R² values above 0.50. Results highlight the potential of integrating behavioral data into educational analytics. This research contributes methodological innovation by incorporating public interest data to explain academic outcomes, with implications for predictive modeling in education policy and planning.

Advance Sustainable Science Engineering and TechnologyVol. 7(4)
State University of Medan (ID), Telkom University (ID)
Openalex Percentile: Top 66%
Islamic Finance and Banking Studies
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