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All Journal MEDIA PETERNAKAN - Journal of Animal Science and Technology Indonesian Journal of Geography BANGUNAN (Jurnal Berkala Jurusan Teknik Sipil UM) Inersia : Jurnal Teknik Sipil dan Arsitektur Economic Journal of Emerging Markets Bumi Lestari Jurnal Masyarakat Informatika Statistika Jurnal Sains dan Seni ITS IPTEK Journal of Science IPTEK The Journal for Technology and Science Jurnal Matematika & Sains Jurnal Dinamika Hukum JURNAL SOSIAL HUMANIORA (JSH) Jurnal Ilmiah Pangabdhi KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Elementer (Elektro dan Mesin Terapan) Jurnal Inotera Jurnal Teknologi & Industri Hasil Pertanian community: Pengawas Dinamika Sosial AL-HAYAT: Journal of Biology and Applied Biology SCAFFOLDING: Jurnal Pendidikan Islam dan Multikulturalisme Jurnal Ilmiah Biologi Eksperimen dan Keanekaragaman Hayati (J-BEKH) International Journal of Ethno-Sciences and Education Research Buletin Ekonomika Pembangunan Journal of Management and Creative Business Journal for Quality in Public Health Jurnal INFOTEL Jurnal Riset Rumpun Ilmu Pendidikan (JURRIPEN) Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi CommunityServiceAkseprinJournal
Sutikno Sutikno
Department Of Statistics, Institut Teknologi Sepuluh Nopember Surabaya
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Journal : IPTEK The Journal for Technology and Science

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Bayes Wavelet Regression Approach to Solve Problems in Multivariable Calibration Modeling Setiawan Setiawan; Sutikno Sutikno
IPTEK The Journal for Technology and Science Vol 21, No 2 (2010)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v21i2.30

Abstract

In the multiple regression modeling, a serious problems would arise if the independent variables are correlated among each other (the problem of ill conditioned) and the number of observations is much smaller than the number of independent variables (the problem of singularity). Bayes Regression (BR) is an approach that can be used to solve the problem of ill conditioned, but computing constraints will be experienced, so pre-processing methods will be necessary in the form of dimensional reduction of independent variables. The results of empirical studies and literature shows that the discrete wavelet transform (WT) gives estimation results of regression model which is better than the other preprocessing methods. This experiment will study a combination of BR with WT as pre-processing method to solve the problems ill conditioned and singularities. One application of calibration in the field of chemistry is relationship modeling between the concentration of active substance as measured by High Performance Liquid Chromatography (HPLC) with Fourier Transform Infrared (FTIR) absorbance spectrum. Spectrum pattern is expected to predict the value of the concentration of active substance. The exploration of Continuum Regression Wavelet Transform (CR-WT), and Partial Least Squares Regression Wavelet Transform (PLS-WT), and Bayes Regression Wavelet Transform (BR-WT) shows that the BR-WT has a good performance. BR-WT is superior than PLS-WT method, and relatively is as good as CR-WT method.
Statistical Downscaling Output GCM Modeling with Continuum Regression and Pre-Processing PCA Approach Sutikno Sutikno; Setiawan Setiawan; Hendy Purnomoadi
IPTEK The Journal for Technology and Science Vol 21, No 3 (2010)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v21i3.41

Abstract

One of the climate models used to predict the climatic conditions is Global Circulation Models (GCM). GCM is a computer-based model that consists of different equations. It uses numerical and deterministic equation which follows the physics rules. GCM is a main tool to predict climate and weather, also it uses as primary information source to review the climate change effect. Statistical Downscaling (SD) technique is used to bridge the large-scale GCM with a small scale (the study area). GCM data is spatial and temporal data most likely to occur where the spatial correlation between different data on the grid in a single domain. Multicollinearity problems require the need for pre-processing of variable data X. Continuum Regression (CR) and pre-processing with Principal Component Analysis (PCA) methods is an alternative to SD modelling. CR is one method which was developed by Stone and Brooks (1990). This method is a generalization from Ordinary Least Square (OLS), Principal Component Regression (PCR) and Partial Least Square method (PLS) methods, used to overcome multicollinearity problems. Data processing for the station in Ambon, Pontianak, Losarang, Indramayu and Yuntinyuat show that the RMSEP values and R2 predict in the domain 8x8 and 12x12 by uses CR method produces results better than by PCR and PLS.
Co-Authors Abdul Mujib Abdullah Hasibuan Adam Astiti Adi Wibowo Afrizal Tjoetra Alda Faujan Alfitriana Purba Ambariyanto Ambariyanto Arfriani Maifizar Arie Wardhono Asih Sukowati Asni Furoida Bambang Sabariman Byba Melda Suhita C Sumantri Chamariyah Chamariyah Chundakus H Darojat Darojat Dede Sahrul DEWI SARTIKA Dewi Susan Dhamang Mahindra Prihantoko Eka Afriandi fadhal fadhal Fandri Sofiana Fastanti Halimul Maduwu Helmie Arif Wibawa Hendy Purnomoadi Henny Oktavianti Heru Hendrayana Indra Waspada Indriyati Indriyati Irene Bella Pramono Karina Oktaviana Khairil Fitryadi Khoirul Nisa Kushartantya Kushartantya Langgeng Wahyu Santosa M A Chozin M Yamin M. Akhyar M. Widyastuti M. Zainuddin Marniza Marniza Meri Fitri Yanti Muhammad Anhar Pulungan Muhammad Luthfi Muhammad Nurif Nanti Musita Nasruddin Harahap Neti Yuliana Niken Wirasanti Norita Butarbutar Novita Sari Nurhaslita nurhaslita Purhadi Purhadi Purwanto Purwanto R. Rijanta Raditya Lucky Riswanto Rahmat Kartolo Ramadani, Mery Rizky Cahyani Roemintoyo Roemintoyo Rokhana Dwi Bekti Sandu Siyoto Sanyoto Sanyoto Sari Suka Wati Setiajeng Kadarsih Setiawan Setiawan Sinta Berliana S Soedarso Soedarso Sudarmadji Sudarmadji Sudarti . Sukatiman Sukatiman Suwarno Suwarno Syarifah R M Timbul Haryono Utaminingsih Utaminingsih Wasis Budiarto Windiani Windiani Yanmesli Yanmesli Yayan Supriyanti Zainal Arifin Zaki Fuadi Zakik, -