Prediksi Penambahan Kasus Covid-19 di Puskesmas Pesantren II Kota Kediri dengan Menggunakan Metode Exponential Smoothing - Aryanti Dwi Astuti Damayanti; Mohamad Anis Fahmi (Ficco Public Health Journal, 2024)
Background: Since the first case in Wuhan, there has been a daily increase in COVID-19 cases in China, peaking between late January and early February 2020. One method that can be used for time series data is exponential smoothing. The aim of this research is to predict the increase of COVID-19 cases at Pesantren II Health Centre in Kediri City using the exponential smoothing method. Methods: This research is a descriptive observational study. The research site is UPTD Islamic Boarding School II Community Health Centre. Data collection techniques were carried out using secondary data and primary data. The secondary data used are COVID-19 cases. Results: Based on the plot results above, it shows that the pattern of COVID-19 incidence has increased over a period of time. Based on the resulting Sum Square Error (SSE) value, where the lowest SSE value indicates that the method is suitable for use. Based on the table above, the best model is double exponential smoothing as it produces the lowest SSE value, 17931.84. Descriptively, it shows that the incidence of COVID-19 increases each month. Conclusion: Forecasting from 2022 to 2023, the number of COVID-19 cases at the Islamic Boarding School II Health Centre will increase using the double exponential smoothing method. People are expected to be able to start a new lifestyle, not underestimate the information and news circulating, and follow the advice and infrastructure in the situation and conditions of the COVID-19 pandemic.