IMPLEMENTASI AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) DALAM PREDIKSI JUMLAH PENDUDUK MISKIN KOTA TANJUNGPINANG

Musliha, Musliha (Department of Informatics Engineering, Universitas Maritim Raja Ali Haji)
Nurfalinda, Nurfalinda (Universitas Maritim Raja Ali Haji)
Rathomi, Muhamad Radzi (Universitas Maritim Raja Ali Haji)

Faktor Exacta
Vol 18, No 4 (2025)

Poverty is one of the main development issues faced by developing countries, including Indonesia. In Tanjungpinang City, located in the Riau Islands Province, the poverty rate in 2022 reached 27.54 thousand people. Therefore, this study aims to predict the number of poor people in Tanjungpinang City using the Autoregressive Integrated Moving Average (ARIMA) method. The data used is monthly time series data from 2015 to 2022, totaling 96 data points. The analysis process begins with stationarity tests, differencing, and selecting the best ARIMA model. The best model identified is ARIMA (1,2,0). Evaluation results indicate that this model has a Mean Absolute Percentage Error (MAPE) of 10.6%, signifying a good level of prediction accuracy. The predicted number of poor people for January 2023 is 18.302 thousand. This research is expected to serve as a reference for the government in designing strategic policies to address poverty in Tanjungpinang City.