Probability Analysis of Educated Unemployment Among Generation Z in West Sumatra
DOI:
https://doi.org/10.37385/ceej.v7i4.10603Keywords:
Educated Unemployment, Generation Z, Sakernas, Logistic Regression, Labor MarketAbstract
Educated unemployment among young people is a serious challenge in the Indonesian labor market, especially amid increasing participation in secondary and higher education. This phenomenon is increasingly relevant to Generation Z, which is in the transition phase from education to the world of work. This study aims to analyze the factors that influence the probability of educated unemployment among Generation Z in West Sumatra Province. The data used is microdata from the 2024 National Labor Force Survey (Sakernas) with individual Generation Z units of analysis having a minimum education level of high school or equivalent. The analysis method used is logistic regression (logit) to estimate the probability of individuals experiencing unemployment, supplemented with an interpretation of odds ratios and average marginal effects. Independent variables include education level, participation in job training, internet access, gender, status in the household, age, and region of residence. The estimation results show that diploma and bachelor's degree levels significantly increase the probability of unemployment compared to high school graduates, while participation in job training and internet access tend to reduce the probability of unemployment. Demographic factors such as gender, household status, and place of residence also play a significant role in determining the unemployment status of Generation Z. These findings indicate a mismatch between educational qualifications and labor market needs at the regional level. This study provides important policy implications related to strengthening vocational education, improving the quality of job training, and expanding access to digital-based labor market information for educated youth.
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