Visualization and Prediction The Number of Patients Visit in Curug Health Center
DOI:
https://doi.org/10.33379/gtech.v8i3.4245Keywords:
Accuracy, Autoregressive Integrated Moving Average (ARIMA), Linear Regression, Prediction, Single Exponential SmoothingAbstract
The problem with this research is the services provided by Puskesmas Curug seem to have excessively long waiting times. In light of this problem, it is imperative to establish a forecast in order to improve the readiness of healthcare facilities in delivering patient care. The forecast for the number of patient visits at Puskesmas Curug was made using data from the years 2015-2018, including visits from both the general public and those covered by the BPJS. Three techniques, specifically linear regression, single exponential smoothing, and autoregressive integrated moving average, are utilised to predict and ascertain the most precise forecasting accuracy. Furthermore, this study has created a representation that can be used by the Curug health centre. The research findings suggest that the ARIMA technique demonstrated the highest level of accuracy, with a precision rate of 73%. The visualisation result will be transmitted to the Puskesmas and then evaluated.
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