Analysis of Economic Growth with Spatial Interaction Between Regions in Indonesia

This study employs a quantitative research approach with a descriptive methodology to analyze spatial interconnections between provinces in Indonesia. The research utilizes panel data regression, assisted by EViews software, and a Spatial Autoregressive (SAR) fixed effects model using R software. The spatial panel regression testing results indicate that the SAR fixed effects model is the most appropriate. The findings reveal that inflation (X1), exports (X3), and national health insurance (X6) have significant effects on economic growth. Global spatial autocorrelation was analyzed using the Moran Index and the Local Indicator of Spatial Autocorrelation (LISA) to identify provinces with spatial autocorrelation from 2019 to 2023. For inflation, 13 provinces exhibit spatial interconnections, namely West Java, Central Java, DI Yogyakarta, North Sumatra, North Maluku, Papua, Bengkulu, Bangka Belitung Islands, West Kalimantan, DKI Jakarta, West Sumatra, Jambi, and South Sumatra. For exports, 11 provinces demonstrate significant spatial interconnections, including West Java, Central Java, Lampung, South Sumatra, Jambi, North Maluku, Bengkulu, Bangka Belitung Islands, DI Yogyakarta, Papua, and Southeast Sulawesi. Meanwhile, for national health insurance, 11 provinces show significant spatial interconnections: Southeast Sulawesi, West Sumatra, Papua, Riau, Bengkulu, Jambi, South Sumatra, Bangka Belitung Islands, Riau Islands, West Kalimantan, and North Kalimantan.