Judul: Pendugaan parameter model AMMI dengan komputasi menggunakan pendekatan bayes, Parameter estimation of ammi models with computation using  bayesian approach
Abstrak: Statistics on the application of plant breeding research has long used primarily in quantitative genetics. Modeling requirements for selection is needed to support efforts to obtain improved varieties. In modeling, there are two main paradigms used to estimate model parameters as the frequentist and Bayesian. Standard AMMI is a classical method has been used extensively for modeling and analysis genotype and environmental interactions. Homogeneity variance error is one of assumptions that must be satisfied in this method. Heterogeneity of variance error can lead to errors in conclusions regarding treatment effect. This study focuses attention on the computational efficiency of Bayesian in AMMI model parameters assumed in the data with heterogeneous variance error and evaluate the suitability of the configuration of genotype and environment interactions in Biplot AMMI. In the data with heterogeneous variance error, there are various differences between the treatment which is likely to cause a reduction in the efficiency of variance estimators in suspected treatment effect. Data transformation is usually used to overcome the problem of heterogeneity variance error. However, it is often quite difficult to obtain a suitable transformation and interpretations of treatment effect obtained from the transformation of data. Therefore we need another approach that can overcome the problem of heterogeneity variance error. The continued development of computerization, the Bayesian approach is a method that has been used to estimate parameters of linier-bilinier model. Bayesian approach is utilizing prior information about parameters to be expected and information from the sample that will be combined to get a posterior distribution. In this paper was evaluated the use of Bayesian approach to estimate model parameters and configuration AMMI biplot. There are two types of data used in this study, the simulated data and real data results of multilocation trials. Each type of data has homogeneous and heterogeneous variance. Prior distribution was a conjugate prior and values for posterior distribution were estimated by Gibbs sampling algorithm. The analysis showed that the Bayesian approach was quite efficient to estimate genotype and environment interaction effect. In fact, AMMI-BS using the BIC to determine the number of principal components of the interaction has a higher efficiency than AMMI-B. Bayesian approach to efficient enough in assuming an interaction effect can be seen from the variance that are smaller than standard AMMI. If the estimation of bilinier components of each method is used to construct the AMMI biplot to know the configuration of interaction structure, there are relatively similar in configuration among the three methods.
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Judul: Pendekatan bayes untuk pendugaan pengaruh interaksi dalam model AMMI
Abstrak: Percobaan multilokasi mempunyai peranan penting dalam perkembangbiakan tanaman dan penelitian agronomi. Kajian mengenai interaksi antara genotipe dan lingkungan diperlukan dalam penyeleksian genotipe yang akan dilepas. Metode statistika yang biasa digunakan untuk mengolah data hasil percobaan multilokasi salah satunya adalah AMMI (Additive Main Effect and Multiplicative Interaction). Metode ini menggabungkan analisis ragam aditif bagi pengaruh utama perlakuan dengan analisis komponen utama pada pengaruh interaksinya. Data percobaan multilokasi yang dikumpulkan dari beberapa tahun di beberapa musim tanam, dianalisis secara terpisah. Agar informasi dari data percobaan multilokasi dapat diperoleh secara lebih menyeluruh, maka perlu adanya suatu analisis yang menggabungkan informasiinformasi dalam beberapa tahun tersebut. Salah satu alternatif analisis yang dapat kita gunakan adalah pendekatan Bayes. Metode ini memanfaatkan informasi awal tentang parameter yang akan diduga dan informasi dari contoh. Hasil simulasi menyatakan bahwa pendugaan dengan metode Bayes menghasilkan dugaan yang lebih baik, karena nilai MSE dugaan Bayes yang lebih kecil dibandingkan dengan MSE dugaan pengaruh interaksi menggunakan metode MKT. Hasil klasifikasi genotipe menggunakan Biplot AMMI menyatakan bahwa, jika informasi prior yang dipilih tepat maka klasifikasi genotipe menggunakan penduga Bayes relatif tidak berbeda dengan klasifikasi genotipe pada kondisi sesungguhnya.
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Judul: Elektrodeposisi Film Tipis Semikonduktor Cu2ZnSnS4 (CZTS) pada Substrat Kaca ITO
Abstrak: Semiconductor Cu2ZnSnS4 (CZTS) thin film that can be used as absorber layers on solar cell module was made via electrodeposition method. CZTS thin film was electrodeposited on the surface of a silicate glass coated with a thin layer of indium tin oxide (ITO). Deposition process was done using potentiostatic mode at room temperature with a potential of 1.05 V for 30, 45, and 60 minutes, followed with annealing the film at 2 different temperatures, 500 ºC using furnace and 180 ºC using hot plate, both treatments for 45 minutes in N2/H2S atmosphere. The X-ray difractograms were analyzed using Match 2 program and showed that the CZTS thin films had kesterit crystalline structure, with a low percentage of CZTS phase. The thin film also contained secondary phases such as Cu2S, ZnS, and SnS. The obtained CZTS thin films had a thickness between 1.039 and 1.676 μm. Absorption study showed that the band gap energy of CZTS thin films which was annealed using furnace ranged from 1.50 to 1.52 eV, whereas that annealed using the hot plate was not observed. The band gap energy value showed that CZTS thin films can be used as sunlight absorber layers on solar cell. The formation of CZTS crystal film on this investigation was effectively performed using furnace annealing process at a temperature of 500 ºC with deposition time of 45 minutes.
Keyword: Thin film, Electrodeposition, Cu2ZnSnS4