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

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

Advance Sustainable Science, Engineering and Technology (ASSET)
Vol. 7 No. 4 (2025): August-October

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.