PENCARIAN MOTHER WAVELET TERBAIK UNTUK ANALISIS PREDIKSI HASIL SAHAM
| Main Authors: | , NIDA UL HASANAH, , Dr. Agfianto Eko Putra, M.Si. |
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| Format: | Thesis NonPeerReviewed |
| Terbitan: |
[Yogyakarta] : Universitas Gadjah Mada
, 2013
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| Subjects: | |
| 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 |
Daftar Isi:
- 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.