Sumertajaya, I Made
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FORUM STATISTIKA DAN KOMPUTASI Vol. 15 No. 1 (2010) - Articles
Multi-locations trials play an important role in plant breeding and agronomic research. Study concerning genotype-environment interaction is needed in the selection of genotype to be released. AMMI (Additive Main Effect and Multiplicative Interaction) is one of the statistical techniques used to analyze data from multi-locations trials. The analysis of AMMI is a combination of analysis between additive main effect and principal component analysis. Multi-location sampling data which were collected several years on several planting season used these analyzed separately. To obtain more comprehensive information of multi-location sampling data, an analysis which combines all of the information through out the years are needed. One of the alternatives is the Bayesian approach. This method utilizes initial information on the estimated parameters and information from samples. The simulation states that prediction with Bayesian methods will produce a better estimator, because the MSE of the Bayesian estimator is smaller than the MSE estimator generated using least squares method.
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FORUM STATISTIKA DAN KOMPUTASI Vol. 15 No. 1 (2010) - Articles
Additive Main Effects Multiplicative Interaction (AMMI) is a widely known analysis used in understanding genotype and environment interaction (GEI) in plant breeding research. The interpretation of AMMI based on biplot visualizes the first two component of principle components analysis. Biplot of AMMI is only an exploration analysis and it does not provide the hypothesis testing, so it can conduct different interpretation by plant breeding researchers. The aim of this research is to find a systematic approach through bootstrap resampling method. Bootstrap resampling method in AMMI model produces confidence region of the first two interaction principle component ( and ) for genotype and environment respectively. Bootstrap confidence region of and estimated the stability of genotype, thus making AMMI analysis more precise and realiable for characterization and selection of genetic environment.
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FORUM STATISTIKA DAN KOMPUTASI Vol. 16 No. 1 (2011) - Articles
PENGARUH PEMILIHAN ARAH ACUAN 00 DAN ARAH ROTASI PADA ANALISIS KORELASI DAN REGRESI LINIER-SIRKULAR (STUDI KASUS: PETA KAWASAN RAWAN BENCANA LETUSAN GUNUNG
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FORUM STATISTIKA DAN KOMPUTASI Vol. 12 No. 1 (2007) - Articles
ANALISIS KONJOIN: METODE FULL PROFILE DAN CBC UNTUK MENELAAH PERSEPSI MAHASISWA TERHADAP PILIHAN PEKERJAAN
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FORUM STATISTIKA DAN KOMPUTASI Vol. 12 No. 1 (2007) - Articles
KLASIFIKASI GENOTIPE PADA DATA TIDAK LENGKAP DENGAN PENDEKATAN MODEL AMMI
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FORUM STATISTIKA DAN KOMPUTASI Vol. 18 No. 1 (2013) - Articles
SURVIVAL ANALYSIS OF CUSTOMER IN POSTPAID TELECOMMUNICATION INDUSTRY
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FORUM STATISTIKA DAN KOMPUTASI Vol. 17 No. 2 (2012) - Articles
PENDUGAAN SELANG KEPERCAYAAN BOOTSTRAP BAGI ARAH RATA-RATA DATA SIRKULAR (Bootstrap Confidence Interval Estimation of Mean Direction for Circular Data)
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FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015) - Articles
MODELLING OF FORECASTING MONTHLY INFLATION BY USING VARIMA AND GSTARIMA MODELS
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