Prediksi Volume Sampah di TPSA Banyuurip Menggunakan Metode Backpropagation Neural Network

Wahyu Santoso (Universitas Muhammadiyah Magelang, Magelang)
Maimunah Maimunah (Universitas Muhammadiyah Magelang, Magelang)
Pristi Sukmasetya (Universitas Muhammadiyah Magelang, Magelang)

JURNAL MEDIA INFORMATIKA BUDIDARMA
Vol 7, No 1 (2023): Januari 2023

The current waste problem is an important issue in many big cities, including Magelang City. The increasing rate of population growth and the decreasing land area for Banyuurip TPSA also makes it difficult for the government to handle waste, causing a negative impact on the environment around the TPSA. Therefore it is necessary to have a prediction of the volume of waste that enters TPSA every day using the Backpropagation Neural Network method so that it can assist the government in preparing budgets, preparing cleaners and estimating the capacity of TPSA in the future. The data used is time series data in the form of waste volume at Banyuurip TPSA from 2019 to 2022. From the results of the Backpropagation Neural Network method with parameters 30-7-1 and 1000 epochs, the best MSE value is 0.018870. The results of the training will then be used to predict the volume of waste the next day.