Zero Inflated Poisson Regression for Analyzing Excess Zeros in Job Transition Data: A Case Study of Tourism Workers in Malang Regency - Berliana, Sarni Maniar; Karim, Rafidah Abd; Yuliana, Rita; Budyanra, Budyanra; Prasetyo, Achmad; Kusuma, Arya Candra; Priatmadani, Priatmadani (UIN Sumatera Utara, 2025)
This study examines job transition patterns among 868 tourism workers in Malang, Indonesia, a key tourism hub, using 2023 Fieldwork Training data from Politeknik Statistika STIS. It aims to model transitions while addressing the high number of workers with no job changes using a Zero-Inflated Poisson (ZIP) model, which better captures these patterns than standard models. The ZIP model, including sex, age, relationship to the head of household, education, and foreign language proficiency, shows that proficient workers are more likely to remain in stable roles, while men and younger workers exhibit greater mobility, particularly when leveraging language skills. These findings support Indonesia’s Sertifikasi Kompetensi SDM Pariwisata program by justifying targeted interventions: language training to enhance mobility for non-proficient workers, mentorship for female tour guides to address gender disparities, and digital skills programs for older workers to boost employability. These strategies align with government efforts to strengthen Malang’s tourism workforce resilience.