Time Series Analysis of Outpatient Hospital Visit Rates in Madiun City

Rohmat ., lina alfiyani


Time efficiency and quality of medical care are indicators of the quality of hospital services. Delays in health services are a problem that is the focus of attention in evaluating the quality of hospital services. Forecasting analysis is used as one method to obtain data sources in the evaluation of comprehensive service quality policies to minimize service delays in the event of a surge in patient visits. The design of this research study is retrospective. The research variable is the number of hospital outpatient visits symbolized by Y. The data used is outpatient visit data from 2017 to 2022. Data for the first two years (years 2017 to 2018) were used to build the demand forecast model, while those from the last three years were used to evaluate the model. Outpatient visit data is a time series count data with discrete values. The data analysis method uses time series analysis with the SPSS 22 program. The results of the time series analysis show that the Y value is 14,710,142. It is hoped that it can be the focus of attention so that when there is a surge in cases, service management can minimize long waiting times.


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