Population data management in Wawonduru Village is currently not running optimally due to a lack of supporting technology, where data management is still done manually by visiting house to house. With the increasing population every year, a system is needed that can manage data efficiently to monitor population fluctuations. This research aims to develop a web-based birth, death and poverty forecasting system to predict population trends and plan appropriate policies in the future in Wawonduru Village. The system was developed using the Personal Extreme Programming (PXP) model and forecasting using the Autoregressive Integrated Moving Average (ARIMA) method. ARIMA was chosen because it is able to accurately predict data with changing patterns and seasonality based on historical patterns. The results show that the developed system not only runs well without errors but also functions as an integrated birth, death and poverty forecasting system. Forecasting using ARIMA resulted in MAPE values of 38.16% for births, 40.67% for deaths, and 44.4% for poverty. It is within the range between 20-50%, so it is feasible to use. Blackbox testing also states that the system has run well and meets user needs both in terms of convenience. So that this system can be used by the Wawonduru Village command to do forecasting to assist in forecasting.