PREDIKSI PENGGUNAAN LISTRIK PADA SEBUAH RUMAH MENGGUNAKAN LONG SHORT-TERM MEMORY

PUTRA, ANANDA MEILIZAR DWI and Arsalan, Osvari (2023) PREDIKSI PENGGUNAAN LISTRIK PADA SEBUAH RUMAH MENGGUNAKAN LONG SHORT-TERM MEMORY. Undergraduate thesis, Sriwijaya University.

	Text RAMA_55201_09021281823048.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (2MB) | Request a copy
	Text RAMA_55201_09021281823048_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (5MB) | Request a copy
	Text RAMA_55201_09021281823048_0028068806_01_front_ref.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (728kB) | Request a copy
	Text RAMA_55201_09021281823048_0028068806_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (303kB) | Request a copy
	Text RAMA_55201_09021281823048_0028068806_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (230kB) | Request a copy
	Text RAMA_55201_09021281823048_0028068806_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (346kB) | Request a copy
	Text RAMA_55201_09021281823048_0028068806_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (474kB) | Request a copy
	Text RAMA_55201_09021281823048_0028068806_06.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (9kB) | Request a copy
	Text RAMA_55201_09021281823048_0028068806_07_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (78kB) | Request a copy
	Text RAMA_55201_09021281823048_0028068806_08_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (629kB) | Request a copy

Abstract

Prediction, also known as forecasting, is the process of estimating events that will occur in the future. In this research, software is developed that can predict electricity usage in a house using the Long Short-term Memory method, which is a Recurrent Neural System designed to overcome vanishing gradient problem. In this research, the model training is done with 2 configurations: split train-validation data into 80%-20%, split cross validation, for 2 model architectures: 2 layer LSTM and 3 layer LSTM each trained with 100, 150, and 200 epochs to see which configuration produces a model with the lowest prediction error. The results showed that the model trained using the split cross validation configuration epoch 150 with 3 layer LSTM had the lowest prediction error among the other configurations with an RMSE of 3.616.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Prediction, Long Short-term Memory, Split Cross Validation, RMSE, Prediction Error.
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	ANANDA MEILIZAR DWI PUTRA
Date Deposited:	14 Aug 2023 06:48
Last Modified:	14 Aug 2023 06:48
URI:	http://repository.unsri.ac.id/id/eprint/127129

Actions (login required)

View Item