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All Journal FORUM STATISTIKA DAN KOMPUTASI Teknotan: Jurnal Industri Teknologi Pertanian Jurnal Ilmu Dasar Jurnal Forum Nuklir IPTEK The Journal for Technology and Science Althea Medical Journal Perspektif : Review Penelitian Tanaman Industri Interest : Jurnal Ilmu Kesehatan ECSOFiM (Economic and Social of Fisheries and Marine Journal) Jurnal NERS Nursing News : Jurnal Ilmiah Keperawatan Jurnal IPTEK Jurnal Keterapian Fisik OIKOS: Jurnal Kajian Pendidikan Ekonomi dan Ilmu Ekonomi International Journal of Nursing and Health Services (IJNHS) Jurnal Ilmu Kebidanan (Journal of Midwivery Science) Journal of Nursing Care Ecopreneur.12 AL-ULUM: JURNAL SAINS DAN TEKNOLOGI JPP Jurnal Kesehatan Poltekkes Palembang Medika Kartika : Jurnal Kedokteran dan Kesehatan Jurnal Ilmiah Permas: Jurnal Ilmiah STIKES Kendal Perspektif, Review Penelitian Tanaman Industri J-PEN Borneo : Jurnal Ilmu Pertanian Among : Jurnal Pengabdian Masyarakat Jurnal Ilmu Faal Olahraga Indonesia MANAJEMEN Jurnal Paradigma Akuntansi Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmu Kebidanan (Journal of Midwivery Science) IQTISHADequity jurnal MANAJEMEN Journal of Global Pharma Technology Jurnal Motivasi Pendidikan dan Bahasa JURNAL MULTIDISIPLIN ILMU AKADEMIK Edumaspul: Jurnal Pendidikan
Setiawan Setiawan
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Journal : iptek the journal for technology and science

 1 
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.
The Jackknife Interval Estimation of Parametersin Partial Least Squares Regression Modelfor Poverty Data Analysis Pudji Ismartini; Sony Sunaryo; Setiawan Setiawan
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.v21i3.42

Abstract

One of the major problem facing the data modelling at social area is multicollinearity. Multicollinearity can have significant impact on the quality and stability of the fitted regression model. Common classical regression technique by using Least Squares estimate is highly sensitive to multicollinearity problem. In such a problem area, Partial Least Squares Regression (PLSR) is a useful and flexible tool for statistical model building; however, PLSR can only yields point estimations. This paper will construct the interval estimations for PLSR regression parameters by implementing Jackknife technique to poverty data. A SAS macro programme is developed to obtain the Jackknife interval estimator for PLSR.
Spatial Econometric Model for Economics Development in Archipelago of Riau, as a Defense System Development in Republic of Indonesia Susanti Linuwih; Setiawan Setiawan; Dwiatmono A. W Dwiatmono A. W; Wiryadi Wiryadi
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.v21i3.40

Abstract

Province of Archipelago of Riau is a region in Indonesia which is adjacent to Singapore and Malaysia. This province has a great potential conditions diversity and natural resources. Planning on public prosperity improvement is necessary in order to increase loyalty and nationalism to Republic of Indonesia. The aim of this research is to build a spatial econometric model of economic growth in Province of Archipelago of Riau. One of the results shows that in recent 4 years Batam always gives the largest contribution to GRDP in Province of Archipelago of Riau. This can be understood that the contribution is more than 72.0% not only based on GRDP at current prices, but also based on GRDP at constant prices. Economic growth rate in regions in Province of Archipelago of Riau is higher than national economic growth rate. The model fits well because the coefficient of determination R2 is more than 85%. There are only 3 worse models, i.e. based on building construction in Batam (with R2= 59.6%), in Tanjungpinang (with R2=74.0%), and based on transportation and communication in Tanjungpinang (with R2=37.1%).
Co-Authors Achmad Fauzi Yahya Adelia, Gita Agung Supangkat ALIMA Alima Alvien Gunawan Aly Diana Ambrosius Purba Andi Nurhabibi Marwil Andi Srimularahmah Andi Tenri Sua Andita Ayu Mandasari Anik Djuraidah Aripin Ponorogo Asbaniar Asbaniar ASEP SAEFUDDIN Asri Dwi Puspitasari Bunyamin Bunyamin Diah Priyantini Dwi N A Dwiatmono A. W Dwiatmono A. W Elsi Dwi Hapsari Elvine Gunawan Eni Endaryati Evi Rahmawati Fahmi Arti Fahrurrozi A. Fahrurrozi Fahrurrozi Firda Inayah Firda Yunara Gaga Irawan Nugraha Gatot Basuki Hari Mukti Gunawan, Alvien Hadi Suryono Hadiyatussalamah Pusfa Kencanasari Hafiz Ambyo Bagaskoro Hanna Goenawan Hargiani, Fransisca Xaveria Hendy Purnomoadi Henryanto Wijaya Ica Elvina Imama Z Imas Rafiyah Imelda Sirait Indah Nur Aini Irma Ruslina Defi Ismail Astar Juliyani Juliyani Juliyani Juliyani Khairil Anam Khatijah Lim Lim Abdullah Khoirul Ngibad Laila Fauziah Ramadhani Lailatun Ni’mah Lilla Puji Lestari Lola Ilona M. Mudadsir Syatibi M. Rizal Chaidir Marissa Tasya Marlik Maslamah Mei Ayu Setyo Ningrum Miftahudin . Mochammad Machrudi Zakaria Nanang P Ni Luh Putu Inca Buntari Agustini Nova Sylviana Novie Salsabila Nuddin Harahab Nunung N U Nur Basuki Nursalam Nursalam Nurul Amalia Prasetyo Yuli Kurniawan Pudji Ismartini Rahmawaty Alie, Ike Rahmawaty Rahman Renny Nirwana Sari Ricky Anguda Robbi'ul Hamzah Rosihan Rosman Rosina Tarigan Roymond H Simamora Rusmiati Rusmiati Sairun Sairun Sarimun Sarimun Sheila Devi Siti Munfaqiroh Sony Sunaryo Sri Suwarni Sugeng H Sundari Sundari Suryantini Suryantini Susanti Linuwih Sutiarso Sutiarso Sutiarso Sutiarso Sutikno Sutikno Swito Prastiwi Teddy Hidayat Tertianto Prabowo Titing Nurhayati Tony Tony Tri Prayuda Dwipha Surbakti Vivi Kumalasari, Vivi Wiryadi Wiryadi Yulianti Rasud Yuni Susanti Pratiwi