Peramalan Jumlah Sampah di Kabupaten Lombok Timur dengan Metode ARIMA dan Dekomposisi

Wiwit Pura Nurmayanti, Kertanah Kertanah, Siti Hadijah Hasanah, Abdul Rahim, hendrayani hendrayani

Abstract


Abstract

Forecasting is the science of predicting events that will occur using historical data and projecting them into the future with some form of mathematical model that aims to handle and policy in the future. In forecasting there are several methods, two of which are Autoregeressive Integrated Moving Average (ARIMA) and Decomposition. ARIMA is a method developed by George Box and Gwilym Jenkins in 1970. The Decomposition Method is a method that decomposes (breaks) time series data into several patterns, namely trend, cyclical and seasonal, and identifies each of these components separately. Both of these methods can be applied in various fields, one of which is in the field of environmental health, especially data on the amount of waste. Problems related to the amount of waste in East Lombok are still a concern of the government because as the population increases and the needs of the community each year have the potential to cause waste problems. The final disposal site (TPA) in East Lombok is located in Ijo Balit, this TPA is the only one in East Lombok. The purpose of this research is to see which method is the best between ARIMA and Decomposition, and to see the forecasting results of the amount of waste entering TPA Ijo Balit from the best method. Based on the results of the analysis carried out by the Decomposition model, it gives the best performance in terms of the smallest error value so that it can be used for Forecasting and produces an RMSE value of 5201.694, a MAPE of 0.955827 and a MASE of 0.0129691. The results of forecasting using the Decomposition method are that the highest forecast occurs in December, while the lowest occurs in January with a total of 1,439,439 (tons) and 1,117,000 (tons).

Keywords:  Forecasting, ARIMA, Decomposition, Waste

Keywords


Forecasting, ARIMA, Decomposition, Waste

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DOI: https://doi.org/10.37905/jjps.v4i2.19954

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