Implementasi Metode Time Series Dalam Forecasting Penggunaan Satusehat

Abstract

Since the Covid-19 pandemic occurred in Indonesia, the government has made new innovations in the field of technology to help the government and society monitor the spread of Covid-19 in Indonesia. This innovation is the PeduliLindungi application, which has tracking and other features that people always use. The influence of PeduliLindungi has become an obligation for the Indonesian people, but since the endemic, the PeduliLindungi application has changed to the SatuSehat application which functions to integrate Indonesian people's health data. The change in the application from PeduliLindungi to SatuSehat reduced the level of application usage, so this research aims to determine the enthusiasm of the public in using the SatuSehat application as a health platform provided by the government in Indonesia. The research was carried out by predicting the number of users of the SatuSehat application based on user data from October 2022 to February 2023. The forecasted data determined the number of users in the next seven months. The research used the Time Series method with a Single Moving Average (SMA) and Single Exponential Smoothing (SES). The research results are in the form of forecasting calculations used to determine the level of enthusiasm of the community in accepting and using the SatuSehat application. After calculations, it was discovered that the research results showed that SatuSehat application users had decreased from March 2023 – September 2023. Error Forecasting showed that the accurate method for forecasting calculations for SatuSehat application users was the SMA method, which obtained MAD calculation results of 1,895,828,857 and MAPE 8.66%.