Ficco Public Health Journal
Vol. 1 No. 01 (2024): April 2024

Prediksi Penambahan Kasus Covid-19 di Puskesmas Pesantren II Kota Kediri dengan Menggunakan Metode Exponential Smoothing

Damayanti, Aryanti Dwi Astuti (Unknown)
Fahmi, Mohamad Anis (Unknown)



Article Info

Publish Date
27 Apr 2024

Abstract

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.

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Journal Info

Abbrev

publichealth

Publisher

Subject

Public Health

Description

Ficco Public Health Journal is a high quality open access peer reviewed research journal that is published by Ficco Scientific Corner. Ficco Public Health Journal provides a platform that welcomes and acknowledges high quality empirical original research papers in the field of public health written ...