Estimating the Unemployment Rate at Sub-District Level in West Java Province in 2024 Using Hierarchical Bayesian Approach with Cluster Information - Aditya, Randy Daffa; Zukhrufah, Awika; Auliya, Eksis; Widyastuti, Dyah; Lubis, Adrian; Nugraha, Anggie; Muchlisoh, Siti (Proceedings of The International Conference on Data Science and Official Statistics, 2025)
Unemployment is a substantial obstacle to growth in Indonesia, affecting both socialand economic stability. The Unemployment Rate is a crucial metric that quantifies the proportionof the labor force actively pursuing work opportunities. The unemployment rate serves as acritical indicator of labor market imbalances, essential for labor policy formulation andassessment. Nonetheless, unemployment data has limitations, particularly at the micro-level,owing to sample constraints. Small Area Estimation (SAE) can address these constraints. Thisstudy estimates the unemployment rate at the sub-district level in West Java province for 2024utilizing the Hierarchical Bayes Beta methodology and clustering techniques. The modelingresults indicate that most sub-districts exhibit a low to medium unemployment rate, however 21locations demonstrate a very high unemployment rate, ranging from 23.00 percent to 48.06percent.