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Growing Science » Decision Science Letters » Assessing the forecasting model ability in measuring the prevention transmission of COVID-19 pandemic: An application of visibility analysis using Inductive logic

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Decision Science Letters

ISSN 1929-5812 (Online) - ISSN 1929-5804 (Print)
Quarterly Publication
Volume 11 Issue 2 pp. 159-166 , 2022

Assessing the forecasting model ability in measuring the prevention transmission of COVID-19 pandemic: An application of visibility analysis using Inductive logic Pages 159-166 Right click to download the paper Download PDF

Authors: Yuyun Hidayat, Titi Purwandari Sukono, Jumadil Saputra

DOI: 10.5267/j.dsl.2021.11.004

Keywords: Decision making, Forecasting model, Visibility analysis, Transmission prevention measures, Covid-19 pandemic

Abstract: Forecasting is an integral approach due to its ability to make informed act decisions and develop data-driven strategies. It's also used to make decisions related to current circumstances and predictions on future conditions. An integral part has been developed using visibility analysis for COVID-19 Outbreak, a lesson from Indonesia. The author identified that its topic has limited attention, especially in assessing the forecasting models. The issue comes from predicted results that are questionable or cannot be trusted without applying the visibility analysis in the forecasting model. The visibility analysis is required to assess the model's ability to forecast future events. In conjunction with the issue, this paper introduces the analysis of visibility error with the different concepts during model development for the transmission prevention measures in making the decision. This study applied a statistical approach to assess the visibility error of forecasting performance in determining how long periods of forecasting and deciding for transmission prevention measures COVID-19 pandemics. Also, we developed the visibility error of time-variant using inductive logic. The result indicated that the number of data required to perform forecasting work on the basis of forecasting model specifications. In conclusion, this study has been completed to develop the statistical formula for identifying the largest time horizon in forecasting model N = V + 2. Also, this developed model can assist the stakeholder in forecasting the number of transmission prevention and making the decision in case of COVID-19 pandemic.

How to cite this paper
Hidayat, Y., Sukono, T & Saputra, J. (2022). Assessing the forecasting model ability in measuring the prevention transmission of COVID-19 pandemic: An application of visibility analysis using Inductive logic.Decision Science Letters , 11(2), 159-166.

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Journal: Decision Science Letters | Year: 2022 | Volume: 11 | Issue: 2 | Views: 1092 | Reviews: 0

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