Forecasting of Generation of Electronic Waste on Green Community with Statistical Assessment of Numerical Models

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SujinnaKarnasuta, et. al.

Abstract

This research aim on the data collection of electronic waste (e-waste) in case of light bulb and dry battery in 6 building locations on green community of  the Kasetsart university from 2016 to 2020 though these 5 years. The statistical assessment from the data collection case to forecasting with numerical modelling of the Moving average, the Weight moving average, the Simple exponential smoothing and the Holt’s exponential smoothing. The correlation between quantity of light bulb and dry batter y in 5 years  from year 2016 to 2020, the correlation between the quantity e-waste is 0.1127 which mean weak correlation or almost no correlation. Therefore, both light bulb and dry battery have no correlation between them. The forecasting for library location in 2021 indicate that the forecasting value rise at the ending of year 2021. The Holt’s Exponential Smoothing technique predict the emerging quantity in September and drop in October. The other techniques lines are moving around 0 to 10 units. The forecasting e- waste for healthcare facility location in 2021 indicate that quantity of light bulb and dry battery are almost equal in healthcare facility location.  Both predict of light bulb and dry battery in 2021 are high in July and stay around 10 – 20 units after October. The forecasting e-waste for veterinary faculty location in 2021 indicate that the prediction for light bulb in veterinary faculty location in 2021 is high in January and July then stay around 20 – 70 units whole year. In the prediction for dry battery in 2021 is high in July and September then stay around 5 – 20 units. The forecasting e-waste for environment faculty location in 2021 indicate that The prediction for light bulb for environment faculty in 2021 stay around 0 – 8 units. And the prediction for dry battery in 2021 stay around 0 – 5 units. The forecasting e-waste for women’s dormitory location in 2021 indicate that Both of prediction for light bulb and dry batter for women’s dormitory location in 2021 are stable, but only the prediction in May and September are high. The prediction in light bulb for research institute in 2021 is high in the last 3 months of 2021, but Holt’s Exponential Smoothing has high prediction’s line in first 4 months then stable until September then the prediction’s line rises around 10 units. The prediction in dry battery in 2021 is high in January and August then stay under 10 units in 2021.  The research result can prepare for what will happen in the future, gain the valuable in insight, and thee result from prediction methods could decrease cost for the environmental management on the green community on the electronic waste (e-waste).  .

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How to Cite
et. al., S. . (2021). Forecasting of Generation of Electronic Waste on Green Community with Statistical Assessment of Numerical Models. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(11), 3098–3112. https://doi.org/10.17762/turcomat.v12i11.6350 (Original work published May 10, 2021)
Section
Research Articles