ARIMA AS A TOOL FOR EARLY WARNING OF INFLATION IN INDONESIA: SHORT-TERM FORECASTING AND THE CONTEXT OF ECONOMIC STABILITY - Farida Islamiah; Via Amalia; Muh. Qardawi Hamzah (Universitas Ichsan Sidenreng Rappang, 2026)
Inflation is a key macroeconomic indicator affecting purchasing power, investment decisions, and overall economic stability; therefore, reliable forecasts are essential for proactive policy responses. This study aims to develop a monthly inflation forecasting model for Indonesia while interpreting its implications for economic stability. The data consist of Indonesia’s monthly inflation from January 2003 to April 2026 (280 observations) sourced from Bank Indonesia. The analysis applies the Autoregressive Integrated Moving Average (ARIMA) approach using standard steps: stationarity testing, model identification, parameter estimation, diagnostic checking, and forecasting. The results indicate that the series requires first differencing to achieve stationarity, and the most appropriate model based on statistically significant parameters, the lowest Akaike Information Criterion value among valid candidates, and white-noise residual diagnostics is ARIMA (0,1,2). Forecasts for May to December 2026 suggest inflation will fluctuate within a moderate range of 2.12% to 4.50%, peaking in August 2026 at 4.50% and reaching the lowest level in October 2026 at 2.12%. Overall, the projected pattern implies relatively controlled inflation dynamics, providing an early signal that can support price-stabilization policy planning and improve certainty for real-sector production and investment activities.