Forecasting Model for Organic Waste Generation at Administration Cafe in UiTM Tapah Campus

Abstract

This study aims at analyzing, comparing and selecting the best predictive model based on organic waste generation at the UiTM Tapah Campus administration cafe. The data collection period begins Monday through Friday from 4th Mac 2019 until 20th April 2020. There are 2 bins that are labeled as Bin 1 and Bin 2 at the Administration Cafe on the UiTM Tapah Campus. Using the Risk Simulator Software, the Moving Average Model, Exponential Smoothing Model, and Holt-Winters Model were adapted and analyzed. The best model is chosen based on error compare meaning. There are three statistical errors in this study which are used for comparison purposes as RMSE, MSE, and MAD. As a result, the lowest error values for both Bin 1 and Bin 2 are shown on the Moving Average model. Therefore, the Moving Average Model can be concluded at Administration Cafe in UiTM Tapah Campus as the best equipped model based on current organic waste generation. The best model will be used in future at Administration Cafe in UiTM Tapah Campus to predict organic waste generation.

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