Rizal, Imaji Kasih Ayunda (2025) Forecasting Indonesia's Youth Unemployment Rate. Bachelor thesis, Data Science and Society (DSS).
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Abstract
This study aims to efficiently forecast Indonesia’s youth unemployment rate. Youth unemployment is a worldwide socioeconomic challenge. As one of the world’s emerging economies, the distinct conditions, including skill mismatches, prevalence of informal jobs, and regional disparities contribute to youth unemployment. Despite its widespread implications, forecasting this specific demographic has been overlooked. This study addresses this gap by applying univariate time series forecasting models using Python’s PyCaret library. Two modeling approaches were explored: a baseline and a feature-engineered setup incorporating autoregressive lags and seasonal indicators. Models were assessed primarily using MASE and MAPE. While feature engineering improved some models, results varied, with further parameter tuning sometimes leading to overfitting. The tuned Exponential Smoothing model performed best, with a MAPE of 7.11%. These findings can guide targeted interventions to mitigate youth unemployment and promote socioeconomic stability.
| Item Type: | Thesis (Bachelor) |
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| Name supervisor: | Haleem, N. |
| Date Deposited: | 28 Jul 2025 09:45 |
| Last Modified: | 28 Jul 2025 09:45 |
| URI: | https://campus-fryslan.studenttheses.ub.rug.nl/id/eprint/740 |
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