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All Journal PROSIDING SEMINAR NASIONAL Jurnal Statistika Universitas Muhammadiyah Semarang
Vega Zayu Farima
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Decision Sciences, Operations Research & Management Education

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PERAMALAN NILAI TUKAR DOLAR AMERIKA TERHADAP INDONESIA DENGAN MODEL MAXIMAL OVERLAP DISCRETE WAVELET TRANSFORM-AUTOREGRESSIVE MOVING AVERAGE Vega Zayu Farima; Herni Utami
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 6, No 1 (2018): Jurnal Statistika
Publisher : Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Muham

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (211.467 KB) | DOI: 10.26714/jsunimus.6.1.2018.%p

Abstract

Beberapa permasalahan dalam kehidupan sehari-hari perlu untuk diramalkan sebelum diambil keputusan. Nilai tukar mata uang asing yang mempengaruhi kurs Indonesia seperti nilai tukar dolar Amerika sangat perlu diramalkan untuk jangka waktu tertentu. Data kurs memiliki volatilitas yang sangat tinggi dan cenderung tidak stasioner. Transformasi wavelet mampu merepresentasikan informasi waktu dan frekuensi secara bersamaan sehingga dapat digunakan untuk menganalisis data-data nonstasioner. MODWT-ARMA yaitu model hibrid dari Maximal Overlap Discrete Wavelet Transform (MODWT) dan Autoregressive Moving Average (ARMA) yang berhubungan dengan data runtun waktu nonstasioner. Secara teori, nilai detail yang diperoleh dari dekomposisi MODWT adalah stasioner. Hal ini menyebabkan hasil dekomposisi dapat diramalan dengan ARMA. Pada peramalan nilai tukar dolar Amerika terhadap rupiah, diperoleh pemodelan yang fitted dengan data training dan diperoleh nilai MAPE yang kecil yaitu 0.82%. Hal ini mengindikasikan bahwa model gabungan ini efektif untuk menambah keakuratan peramalan.  Kata kunci : Peramalan, Data Runtun Waktu, Dekomposisi, MODWT-ARMA, MAPE.
FORECASTING FREEPORT-MCMORAN STOCK PRICE USING LOCALLY STATIONARY WAVELET Vega Zayu Farima; Indah Manfaati Nur
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2018: PROCEEDING 1ST INSELIDEA INTERNATIONAL SEMINAR ON EDUCATION AND DEVELOPMENT OF ASIA (INseIDEA)
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (514.742 KB)

Abstract

PT Freeport Indonesia is the manager of the Grasberg Mine in Papua, Indonesia, which is one of the largest gold mines in the world. This mine also contains copper and silver for the world market. Freeport McMoRan'sshareholder has recently trending topic because its shares have been purchased by the Indonesian government.This stock price value has a very high volatility and tend not stationary. Wavelet transformation is capable ofrepresenting functions that are not smooth or have high volatility. Locally Stationary Wavelet (LSW) is aforecasting model by minimizing error values and capturing most of the time series data information. In thisresearch we can get stock price of Freeport-McMoran stationary after differencing. Stock price forecasting usingLSW yields a small MAPE value of 1.94%. This indicates that the LSW model is good for forecasting usingstock price data. Keywords: Freeport McMoRan, Stasionary, LSW, MAPE
Co-Authors Herni Utami Indah Manfaati Nur