Implementation of Facebook Prophet Algorithm in Population Prediction - Raditya Dimas Libriawan; Anggraini Puspitasari Sari; Henni Endah Wahanani (Komunitas Dosen Indonesia, 2025)
The number of populations in a country is a very important aspect because it has a direct effect on various aspects of life. Indonesia is in the fourth position of the country with the largest population in the world. It is recorded in the Indonesian Central Statistics Agency (BPS) that by mid-2024, the population in Indonesia will reach 281.603.800 people. The ever-increasing population will drive increased energy demand. Therefore, monitoring and controlling population growth is a crucial and indispensable step, one of which is by utilizing machine learning to conduct time series forecasting. This study contributes by optimizing FB Prophet’s parameter configuration for population forecasting in Indonesia, achieving improved accuracy compared to traditional models. The purpose of this study is to determine the level of accuracy and error of the model with evaluation metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). The results obtained from forecasting using the Prophet algorithm were that Indonesia increased by 1.5% by the end of 2025, with the value of the MAE evaluation metric of 0.0244, RMSE of 0.0256, and MAPE of 2.65%, which indicates a highly accurate prediction level for annual population data.