A Web-Based Forecasting Approach to Estimating the Number of Low-Income Households Eligible for Social Food Aid Using Holt’s Double Exponential Smoothing - Solikhin, Solikhin; Churum, Muhammad Walid Syahrul; Abdillah, M. Zakki; Putra, Toni Wijanarko Adi; Masrur, Mukhamad (Information Systems - Universitas Pesantren Tinggi Darul Ulum, 2025)
This work presents a web-based forecasting methodology for predicting the quantity of low-income households qualified for social food assistance utilizing Holt’s Double Exponential Smoothing (HDES) technique. Precise assessment is crucial for governmental bodies and social welfare organizations to guarantee efficient aid distribution and effective resource allocation. The proposed method amalgamates time series forecasting models with a web-based application to deliver real-time predictions and accessibility for decision-makers. Historical data on low-income household statistics were employed to formulate and authenticate the forecasting model. The findings indicate that HDES delivers dependable short-term predictions with low error rates, accurately reflecting patterns in the data. This online application offers policymakers an effective means for monitoring socio-economic trends and enhancing the responsiveness of social assistance initiatives. This research contributes by integrating statistical forecasting with web-based applications to aid social policy decisions.