Prediksi Tingkat Pengangguran di Wilayah Provinsi Jawa Timur Menggunakan Metode Elman Recurrent Neural Network (ERNN)

Panjaitan, Tompo (2024) Prediksi Tingkat Pengangguran di Wilayah Provinsi Jawa Timur Menggunakan Metode Elman Recurrent Neural Network (ERNN). Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

The unemployment rate is an important indicator for measuring the economic health of a country and the well-being of its society. In the context of Indonesia, the issue of open unemployment poses a serious challenge that needs to be addressed in order to achieve inclusive and sustainable economic growth. Therefore, research was conducted on the application of the Elman Recurrent Neural Network method to predict the unemployment rate in the East Java Province region. The data used consists of the Open Unemployment Rate (TPT) data for East Java Province from 2001 to 2022. This data was transformed into a time series format with 5 variables. The research used 500 epochs, learning rates (α) of 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, and 0.1, and an error tolerance of 0.001. The MSE testing results in this study indicate the smallest MSE value at a learning rate of 0.01 with 90% training data and 10% test data, with an MSE value of 0.061227. Keyword: Unemployment, East Java, Elman Recurrent Neural Network (ERNN) Method.

Item Type:

Thesis (Undergraduate)

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Anggraeny, Fetty Tri	NIDN0711028201	fettyanggraeny.if@upnjatim.ac.id
Thesis advisor	Haromainy, Muhammad Muharrom Al	NIDN0701069503	muhammad.muharrom.if@upnjatim.ac.id

Subjects:

T Technology > T Technology (General) > T58.6-58.62 Management Information Systems

Divisions:

Faculty of Computer Science > Departemen of Informatics

Depositing User:

TOMPO PANJAITAN

Date Deposited:

04 Jun 2024 02:43

Last Modified:

04 Jun 2024 02:43

URI:

https://repository.upnjatim.ac.id/id/eprint/23971