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Armaini Akhirson
Univeritas Gunadarma
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Journal : Jurnal Ekonomi dan Bisnis

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Pendekatan Adaptive Neuro Fuzzy Sebagai Alternatif Bagi Bank Indonesia Dalam Menentukan Tingkat Inflasi Di Indonesia Armaini Akhirson; Brahmantyo Heruseto
Jurnal Ekonomi dan Bisnis Vol 19 No 2 (2016)
Publisher : Fakultas Ekonomika dan Bisnis Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (548.719 KB) | DOI: 10.24914/jeb.v19i2.463

Abstract

In uncertain economic like today, research and modeling the inflation rate is considered necessary to provide estimates and predictions of inflation rates in the future. Adaptive Neuro Fuzzy approach is a combination of  Neural Network and Fuzzy Logic. This study aims to describe the movement ofinflation(output variable ) so it can beestimated by observing four Indonesia's macroeconomic data, namely the exchange rate, money supply, interbank interest rates, and the output gap (input variable). Observation period started from the data in 20011 to 20113. After the learning process is complete, fuzzy systems generate 45 fuzzy rules that can define the input-output behavior. The results of this study indicate a fairly high degree of accuracy with an average error rate is 0.5315.
Co-Authors Akhmad Kahfi, Akhmad Anieq Siti Zahroh Bella Lutfiyya Brahmantyo Heruseto Dionysia Kowanda Fitri Rismiyati Herliana Intan Fandini Irwandaru Dana Jaya Mulya Sari Hadiati Prihandoko, Prihandoko Rehulina Apriyanti Shinta Teviningrum Sunayah Sunayah Veshela Annesa Dewi Nawangwulan