IMPLEMENTASI METODE ARTIFICIAL NEURAL NETWORK (ANN) UNTUK MEMPREDIKSI TINGKAT INFLASI DI INDONESIA DENGAN MENGGUNAKAN RAPIDMINER

CAHYATI, NILAM DWI (2024) IMPLEMENTASI METODE ARTIFICIAL NEURAL NETWORK (ANN) UNTUK MEMPREDIKSI TINGKAT INFLASI DI INDONESIA DENGAN MENGGUNAKAN RAPIDMINER. Other thesis, Universitas Pesantren Tinggi Darul 'Ulum.

	Text cover_compressed.pdf Download (249kB)
	Text BAB I_compressed.pdf Download (131kB)
	Text BAB II _compressed.pdf Download (340kB)
	Text BAB III _compressed.pdf Download (143kB)
	Text BAB IV _compressed.pdf Restricted to Repository staff only Download (234kB)
	Text BAB V _compressed.pdf Restricted to Repository staff only Download (91kB)
	Text DAFTAR PUSTAKA_compressed.pdf Download (108kB)
	Text hasil cek similarity_compressed.pdf Download (145kB)

Abstract

Bank Indonesia defines inflation as a general and sustained increase in prices, which if widespread will potentially affect other price increases resulting in a decrease in the value of money. The purpose of this research is to predict the inflation rate so that inflation can be controlled every month and provide information to the government, especially Bank Indonesia in the decision-making process to determine monetary policy and as an effort to maintain inflation stability in the future. This research implements the Artificial Neural Network (ANN) method with RapidMiner software. In this study using Inflation rate data for 11 years, from the period January 2013 to December 2023. The prediction results using the Artificial Neural Network method for the inflation rate in Indonesia for the period January 2024 to December 2024 are consecutively obtained at 2.26%; 3.96%; 2.44%; 3.3%; 2.95%; 3.26%; 3.54%; 3.37%; 3.56%; 3.51%; 3.84%; 3.73% with an RMSE accuracy value of 0.909. Keywords : Inflation, ANN, RMSE, Rapidmine

Actions (login required)

Downloads

View Item