Sahisnu, Julian Satya and Natalia, Friska and Ferdinand, Ferry Vincenttius and Sudirman, Sud and Ko, Chang Seong (2020) VACCINE PREDICTION SYSTEM USING ARIMA METHOD. ICIC Express Letters, 11 (6). pp. 567-575. ISSN 2185-2766
Full text not available from this repository.Abstract
Indonesia is a country that runs health programs in the form of primary compulsory immunizations for children aged 0-11 months. According to the Health Law, Number 36 of 2009 states that every child has the right to receive primary immunization by the provisions to prevent the occurrence of diseases that can be avoided through immunization. The Indonesian government are also obliged to provide complete immunization to every baby and child by the implementation of immunization contained in the Minister of Health Regulation Number 42 of 2013. The purpose of this study is to predict vaccine stock for immunization needs, and the government can use the application to determine vaccine stock requirements for each clinic so that there is no shortage or excess stock. This prediction can ensure that immunization coverage is well distributed. We can help parties who organize primary immunization activities by making predictions and forecasting results based on the R application. In addition, the application can provide information in the form of predictive analysis. The method used in measuring predictions is ARIMA (Auto-Regressive Integrated Moving Average) to calculate the prediction of immunization.
| Item Type: | Article |
|---|---|
| Keywords: | Inventory forecasting, ARIMA, Immunization, Time series, Data visualization, Vaccine-preventable diseases |
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 001 Knowledge 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 006 Special Computer Methods 600 Technology (Applied Sciences) > 610 Medicine and Health > 614 Forensic Medicine; Incidence of Injuries, Wounds, Disease; Public Preventive Medicine 600 Technology (Applied Sciences) > 610 Medicine and Health > 616 Diseases |
| Divisions: | Faculty of Engineering & Informatics > Information System |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 23 Nov 2021 05:15 |
| Last Modified: | 23 Nov 2021 05:15 |
| URI: | https://kc.umn.ac.id/id/eprint/19252 |
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