PENCARIAN MOTHER WAVELET TERBAIK UNTUK ANALISIS PREDIKSI HASIL SAHAM

Determining the best mother wavelet for share data prediction of Sony 2006 and BNI 2012 has been done. Adaplet method (Adaptive Filter which its initial coefficients using wavelet) is used for prediction. Mother wavelets used are Coiflet 1-5, Daubechies 1-5, Symlet 1-5. The goal is to select the bes...

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Main Authors: , NIDA UL HASANAH, , Dr. Agfianto Eko Putra, M.Si.
Format: Theses and Dissertations NonPeerReviewed
Published: [Yogyakarta] : Universitas Gadjah Mada 2013
Subjects:
ETD
Online Access:https://repository.ugm.ac.id/125871/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=66052
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spelling id-ugm-repo.1258712016-03-04T08:41:01Z https://repository.ugm.ac.id/125871/ PENCARIAN MOTHER WAVELET TERBAIK UNTUK ANALISIS PREDIKSI HASIL SAHAM , NIDA UL HASANAH , Dr. Agfianto Eko Putra, M.Si. ETD Determining the best mother wavelet for share data prediction of Sony 2006 and BNI 2012 has been done. Adaplet method (Adaptive Filter which its initial coefficients using wavelet) is used for prediction. Mother wavelets used are Coiflet 1-5, Daubechies 1-5, Symlet 1-5. The goal is to select the best mother wavelet for prediction result analysis of share data based on analyses. Analyses used including overshoot and pattern conformity, three days prediction, and segmentation. According to the analysis of overshoot, it is shown that for all data, the overshoot at the beginning of data increased as its wavelet level increased. Daubechies 1 and Symet 1 produced smallest overshoot among the other wavelets (112.2%). Error autocorrelation data pattern prediction indicates conformity with the original data. As its wavelet level increased, the error autocorrelation pattern also ramped (near zero). Coiflet 5 and Daubechies 1 produced the smallest mean square error, which is equal to 0.0147. Meanwhile, Coiflet 1 shows the best result with an average error 0.001 in the next three days prediction. On the other hands, Symlet 3 shows the best mean square error of 1.213. By ranking each method in all analysis, it is shown that Symlet offers the best result. [Yogyakarta] : Universitas Gadjah Mada 2013 Thesis NonPeerReviewed , NIDA UL HASANAH and , Dr. Agfianto Eko Putra, M.Si. (2013) PENCARIAN MOTHER WAVELET TERBAIK UNTUK ANALISIS PREDIKSI HASIL SAHAM. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=66052
institution Universitas Gadjah Mada
building UGM Library
country Indonesia
collection Repository Civitas UGM
topic ETD
spellingShingle ETD
, NIDA UL HASANAH
, Dr. Agfianto Eko Putra, M.Si.
PENCARIAN MOTHER WAVELET TERBAIK UNTUK ANALISIS PREDIKSI HASIL SAHAM
description Determining the best mother wavelet for share data prediction of Sony 2006 and BNI 2012 has been done. Adaplet method (Adaptive Filter which its initial coefficients using wavelet) is used for prediction. Mother wavelets used are Coiflet 1-5, Daubechies 1-5, Symlet 1-5. The goal is to select the best mother wavelet for prediction result analysis of share data based on analyses. Analyses used including overshoot and pattern conformity, three days prediction, and segmentation. According to the analysis of overshoot, it is shown that for all data, the overshoot at the beginning of data increased as its wavelet level increased. Daubechies 1 and Symet 1 produced smallest overshoot among the other wavelets (112.2%). Error autocorrelation data pattern prediction indicates conformity with the original data. As its wavelet level increased, the error autocorrelation pattern also ramped (near zero). Coiflet 5 and Daubechies 1 produced the smallest mean square error, which is equal to 0.0147. Meanwhile, Coiflet 1 shows the best result with an average error 0.001 in the next three days prediction. On the other hands, Symlet 3 shows the best mean square error of 1.213. By ranking each method in all analysis, it is shown that Symlet offers the best result.
format Theses and Dissertations
NonPeerReviewed
author , NIDA UL HASANAH
, Dr. Agfianto Eko Putra, M.Si.
author_facet , NIDA UL HASANAH
, Dr. Agfianto Eko Putra, M.Si.
author_sort , NIDA UL HASANAH
title PENCARIAN MOTHER WAVELET TERBAIK UNTUK ANALISIS PREDIKSI HASIL SAHAM
title_short PENCARIAN MOTHER WAVELET TERBAIK UNTUK ANALISIS PREDIKSI HASIL SAHAM
title_full PENCARIAN MOTHER WAVELET TERBAIK UNTUK ANALISIS PREDIKSI HASIL SAHAM
title_fullStr PENCARIAN MOTHER WAVELET TERBAIK UNTUK ANALISIS PREDIKSI HASIL SAHAM
title_full_unstemmed PENCARIAN MOTHER WAVELET TERBAIK UNTUK ANALISIS PREDIKSI HASIL SAHAM
title_sort pencarian mother wavelet terbaik untuk analisis prediksi hasil saham
publisher [Yogyakarta] : Universitas Gadjah Mada
publishDate 2013
url https://repository.ugm.ac.id/125871/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=66052
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