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All Journal Journal of Mathematics and Scientific Computing With Applications
Nurhabidah, Fauziah
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Mathematics

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Analysis of the Accuracy Level of Using the Monte Carlo Method in Predicting the Number of Dengue Fever Sufferers Nurhabidah, Fauziah
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 2 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v5i2.984

Abstract

Dengue fever is an infectious disease that continues to be a threat to public health in Indonesia. The increasing number of sufferers every year requires accurate prediction strategies to support effective prevention and control policies. This study aims to analyze the level of accuracy of the Monte Carlo method in predicting the number of dengue fever sufferers in Indonesia, especially in North Sumatra Province. The data used in this research is data on dengue fever cases from 2021 to 2023 obtained from the Central Statistics Agency (BPS) and the Health Service. The prediction process is carried out using Monte Carlo simulation which involves a probability-based random calculation process. The research results show that the Monte Carlo method has a fairly high level of accuracy in predicting patterns of dengue fever cases, with an accuracy value of 3440 (99.41%) compared to other conventional prediction methods. In addition, this method is proven to be flexible in dealing with variations in fluctuating data patterns. It is hoped that this research can contribute to strategic decision making, especially in mitigating dengue fever through more accurate predictions.
Analysis of the Accuracy Level of Using the Monte Carlo Method in Predicting the Number of Dengue Fever Sufferers Nurhabidah, Fauziah
Journal of Mathematics and Scientific Computing With Applications Vol. 5 No. 2 (2024)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v5i2.984

Abstract

Dengue fever is an infectious disease that continues to be a threat to public health in Indonesia. The increasing number of sufferers every year requires accurate prediction strategies to support effective prevention and control policies. This study aims to analyze the level of accuracy of the Monte Carlo method in predicting the number of dengue fever sufferers in Indonesia, especially in North Sumatra Province. The data used in this research is data on dengue fever cases from 2021 to 2023 obtained from the Central Statistics Agency (BPS) and the Health Service. The prediction process is carried out using Monte Carlo simulation which involves a probability-based random calculation process. The research results show that the Monte Carlo method has a fairly high level of accuracy in predicting patterns of dengue fever cases, with an accuracy value of 3440 (99.41%) compared to other conventional prediction methods. In addition, this method is proven to be flexible in dealing with variations in fluctuating data patterns. It is hoped that this research can contribute to strategic decision making, especially in mitigating dengue fever through more accurate predictions.
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