PREDIKSI HARGA PANGAN MENJELANG RAMADAN MENGGUNAKAN SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE DI SUMATERA SELATAN: FOOD PRICE PREDICTIONS AHEAD OF RAMADAN USING SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE IN SOUTH SUMATRA - Cindy Dinata; Azera Pramesty; RA Aliffyaa Ramadhani; Merizka Azzahra; Ken Ditha Tania; Allsela Meiriza (Rabit : Jurnal Teknologi dan Sistem Informasi Univrab, 2026)
Food price fluctuations ahead of Ramadan in Indonesia are a seasonal phenomenon with a significant impact on regional economic stability. This study aims to develop a price prediction model for five major food commodities, namely medium rice, curly red chili, shallots, chicken eggs, and cooking oil, in South Sumatra Province using the Seasonal Autoregressive Integrated Moving Average (SARIMA) approach. The analysis stages began with stationarity testing of historical data, determining optimal model parameters, and evaluating accuracy using the Mean Absolute Percentage Error (MAPE) method. The results show that the SARIMA model effectively identifies seasonal trends with a very high level of accuracy, evidenced by an error rate of only 1.92% for medium rice. Projections for 2026 indicate that rice and chicken egg prices tend to remain stable, while horticultural products such as red chili show a downward trend. This study concludes that not all food commodities experience price increases before Ramadan; therefore, local government intervention should be conducted selectively based on the characteristics of each commodity. This model can be implemented as an early warning instrument to support economic stability in the South Sumatra region.