Penerapan Metode Artificial Neural Network (ANN) Untuk Peramalan Inflasi Di Indonesia

Ryandhi, Rizky (2017) Penerapan Metode Artificial Neural Network (ANN) Untuk Peramalan Inflasi Di Indonesia. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

[img]
Preview
Text
5213100112_Unergraduate_Theses.pdf - Published Version

Download (3MB) | Preview

Abstract

Nilai inflasi pada sebuah negara merupakan sebuah hal yang patut diperhatikan dan dijaga kestabilannya oleh pemerintah untuk memberikan situasi perekonomian yang kondusif. Bank Indonesia (BI) merupakan lembaga negara yang memegang tanggung jawab tersebut. BI memiliki wewenang untuk mengeluarkan kebijakan moneter dalam menjalankan fungsinya. Saat ini sebagian besar indsutri di Indonesia masih memiliki ketergantungan untuk mengimpor bahan baku dan bahan pendukung untuk proses produksinya. Hal tersebut menimbulkan kerentanan terjadinya inflasi di Indonesia saat negara pengimpor mengalami inflasi. Terjadinya inflasi pada negara mitra dagang mempengaruhi harga bahan baku produksi yang diimpor dari negara tersebut. Kenaikan harga produksi yang merambat ke kenaikan harga produk, merupakan salah satu faktor penyebab terjadinya Cost-push inflation. Penelitian ini bertujuan untuk mengembangkan model peramalan berdasarkan metode Artificial Neural Network, untuk meramalkan tingkat inflasi di Indonesia dengan memperhitungkan variable tambahan yaitu inflasi pada negara mitra dagang. Berdasarkan hasil penelitian variable inflasi pada negara mitra dagang dan nilai rupiah terhadap dollar dapat meningkatkan akurasi peramalan walaupun perbedaannya tidak terlalu signifikan. =============================================================================================== Inflation rate in a country is something that government needs to keep an eye on to maintain its stability in order to create a conducive economic state. In Indonesia, Bank Indonesia (BI) is a legitimate state institutions holding the responsibility on that matter, since BI has the authority to issue a monetary policy. Nowadays most of Industry in Indonesia still relying on imported raw and supporting materials on their production process. That will caused Indonesia to be susceptible to inflation when the importer countries is encountering an inflation. Inflation on trading partners country may affect the price of raw and supporting materials imported from those countries. An increase of production cost that affect on an increasement of the finished product prices, is one caused factor of cost-push inflation. The objective of this research is to develop a forecasting model based on artificial neural network method, to forecast the inflation rate in Indonesia while taking inflation rate in trading partner countries into account as an variable used in the process of forecasting. Judging from the result of the research, it can be said that both variables; inflation on trading partners country and rupiah exchange rate, gives a positive effect for forecasting inflation rate resulting a higher forecasting accuracy.

Item Type: Thesis (Undergraduate)
Additional Information: RSSI 006.32 Rya p-1
Uncontrolled Keywords: Peramalan, Inflasi, Peramalan Inflasi, Artificial Neural Network, ANN, Indonesia
Subjects: H Social Sciences > HB Economic Theory > Economic forecasting--Mathematical models.
Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science)
Divisions: Faculty of Information Technology > Information System
Depositing User: Rizky Rizky Ryandhi
Date Deposited: 31 Oct 2017 01:48
Last Modified: 05 Mar 2019 02:58
URI: https://repository.its.ac.id/id/eprint/42185

Actions (login required)

View Item View Item