ABSTRACT
The spread of COVID-19, apart from being influenced by specific pathogenic factors, is also influenced by population structure and mobility. This study was conducted to develop a forecasting model for the increase in COVID-19 cases due to variations in the holiday calendar and the sun's distance to the earth. This study uses secondary data taken from the East Java Provincial Health Office in collaboration with the East Java Province COVID-19 Task Force. This study uses two independent variables: the Calendar Variation in 2020 and 2021 (X1);The Sun-Earth Distance (X2) and dependent variable (Y) is the Daily Case of COVID-19 in East Java Province from March 2020 to June 2021. The process of data analysis is carried out by analyzing time series data and building a forecasting model with a symbolic time series prognosis approach. The analysis process is carried out using Heuristic Lab 3.3 software. Based on the results of this study, it can be concluded that variations in the holiday calendar and the sun-earth distance have a strong influence on daily cases of COVID-19. The symbolic time series prognosis model obtained has an accuracy rate of up to 90.04% on training data and 82.14% on testing data. © 2023 WITPress. All rights reserved.
ABSTRACT
The contribution of fisheries to the national GDP had increased from 2.32% in 2014 to 2.60% in 2018. However, in 2020, the threat of the Covid-19 pandemic emerged, which hit all sectors of the economy, including the fisheries sector. Many communities, especially coastal fishing communities, are complaining about economic hardship. Income has fallen dramatically because people’s purchasing power has fallen significantly. Based on these problems, this research was conducted to build a fishers’ income prediction model. This research took a case study on fishers in Karanggongso District Trenggalek by surveying 50 fishing households. There were 12 predictors variables, namely Boat Type (X1), Price Boat (X2), Age of the Boat (X3), Boat Power (X4), Machine Price (X5), Engine Life (X6), Fishing Equipment Price (X7), Fishing Gear Life (X8), Cool Box (X9), Trip/week (X10), Average Hours/trip (X11), and Total Expenditures/week (X12). The response variable is Income Per Week (Y). Data analysis was done by using multiple linear regression analysis and flexible modelling with a machine learning approach. Based on the results of the analysis, a multiple linear regression model had an accuracy level of R 2 = 70.5% and MSE = 1.086 × 1018 with the boat price was the most dominant influence on fishers’ income. While flexible modelling has an accuracy level of R 2 = 85.2% and MSE = 3.308 × 1014. From this research, it was proven that the flexible model had a higher level of accuracy than the linear regression model. Also, the flexible model obtained the nonlinear effect on the number of cool boxes and the fishing gear life.