The utilization of deep learning in forecasting the inflation rate of education costs in Malang

Afrah, Ashri Shabrina, Lestandy, Merinda and Juwita, P. R. Suwondo (2023) The utilization of deep learning in forecasting the inflation rate of education costs in Malang. Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer, 7 (1). pp. 93-103. ISSN 2598-3288

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Abstract

The public need information about the predicted inflation rate for education costs to manage family finances and prepare education funds. This information is also beneficial for the government to create policies in edu-cation. The aim of this research is to develop a model to forecast the inflation on education costs in Malang using the Deep Learning Method. This research was conducted using Consumer Price Index (CPI) data for the Education Expenditure Group in Malang in 1996-2021, which was taken from the Central Bureau of Statistics (BPS) Malang. The forecasting method used is the Long and Short-Term Memory (LSTM) method, which is a development of the Recurrent Neural Network (RNN). The results showed that it achieved the best accuracy by a model with 1 hidden layer and 4 hidden nodes, namely MAPE=2.8765% and RMSE=8.37.

Item Type:	Journal Article
Keywords:	deep learning; long short-term memory; education cost; inflation
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	Ashri Shabrina Afrah
Date Deposited:	28 Jul 2023 10:56

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