MODEL VECTOR AUTOREGRESSIVE (VAR) UNTUK PREDIKSI INDEKS HARGA KONSUMEN, HARGA BERAS, DAN INFLASI KOTA SURABAYA - Suprapto, Rheinka Elyana; Trimono, Trimono; Aviolla Terza Damaliana (LPPM Universitas Bina Bangsa, 2025)
The current global economic conditions face increasingly complex challenges, with projections of economic weakness continuing until 2025. Globalization has reduced the role of domestic factors and strengthened the impact of the global economy on the formation of inflation. From a macroeconomic perspective, the level of economic growth is often used as a leading indicator of a country's success, reflecting continuous changes in the economy with the aim of achieving better conditions over a certain period of time. Historically, the inflation rate in Indonesia tends to be higher compared to other developing countries. Data shows that during the 2010–2020 period, Indonesia's quarterly inflation was consistently higher than other developing countries. This study uses time series data analysis with a multivariate approach that includes three main variables: inflation, rice prices, and the consumer price index (CPI). The method used is Vector Autoregressive (VAR), which is an analysis technique for data with more than one related variable. The results of the analysis show that the VAR method produces a Mean Absolute Percentage Error (MAPE) value of 32.73% for inflation, 6.24% for CPI, and 5.78% for rice prices. These findings indicate that the VAR model has varying levels of accuracy for each variable, with more accurate predictions for CPI and rice prices compared to inflation.