Judul: Analisis Ragam Gabungan Dengan Ragam Tidak  Homogen  (Studi Kasus Percobaan Multilokasi Budidaya Jahe Di Jawa Barat)
Abstrak: Combined analysis of variance has several rigid assumptions. One of them is homogeneity of variance which in many cases is failed to be fulfilled. So there should be a statistical approach to handle this problem. Classical liniear model of data from an experiment assumes the homogeneity of variance. If it is violated then usually the data will be transformed to achieve linearity of the model. But one problem in using transformed data is difficulty in interpreting it. Other approach used for handling this problem is organizing the data into groups based on the similarity of variance. One procedure that uses this kind of approach is Mixed Procedure. The objectives of this research were to distinguish the interaction between the little white ginger expected genotype and its cultivation location and to study the technique of handling heterogeneity of variance in Combined Analysis of Variance. The data used in this research was experiments data of little white ginger produced by researcher of Indon Spices and Medical Crops Research Institute (ISMECRI) Bogor. The experiment was conducted in five location: Sukamulya, Wado, Malangbong, Garut, and Majalengka. The single experiment was accomplished by cultivating seven little white ginger expected genotype. The environmental design was Randomize Complete Block Design with three repetitions and the response was the amount of ginger young plants. Three analysis’ of variance with different covariance matrix conclude significant interaction between location and genotype. Log-likelihood ratio of each model covariance matrix was used to select the best model wich turns out to be the model with revision of location groups. The treatment significance test with the assumption that the variance between locations is not homogeny result greater p-value compared to the treatment significance test with revised estimated variance. This means that the treatment significance test with the assumption that the variance between locations is not homogeny has lesser accuracy level than the treatment significance test with revised estimated variance on the same level of significance. Likewise, the treatment significant test with transformed data has lesser accuracy level than the treatment significance test with revised estimated variance. The appropriate organization of the data into groups on the similarity of variance (proper selection of covariance matrix) can increase accuracy of treatment significance test for cases when the variance is not homogeny.
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Judul: Klasifikasi Genotipe Pada Data Tidak Lengkap  Dengan Pendekatan Model Ammi
Abstrak: Multilocations trials play an important role in plant breeding and agronomic research. Study concerning genotype-environment interaction needed in selection of genotype to be released. AMMI (Additive Main effect and Multiplicative Interaction) is one of statistical technique to analyze data from multilocations trials. The analysis of AMMI is a combining analysis between additive main effect and principal component analysis. The main restriction of using AMMI analysis is balance data. However a multilocations trials give an opportunity of the occurrence of unbalance data become very big. It is intended for every combination of genotype and location have the same number of replication. Therefore, we must estimate the data which do not complete. Incomplete data case, it is needed some data estimation method analysis, at this research employed connected data method and EM-AMMI algorithm to estimate incomplete data. Data which used in this research is obtained from Indon Spices Medicinal Crops Research Institute (ISMECRI) Bogor. It is a secondary data of ginger essential content resulted from multilocations trials, sixteen of genotype ginger which tested at five location in West Java. Simulation result shows that estimation using connected data will obtain smaller MAPE if its followed by two times EM-AMMI algorithm, for the percentage of data lose 10% to 20%. Production of ginger essential content estimated with AMMI2 model can explain 76.09% interaction structure among location and genotype. Seen from stability of genotype, there are 2 stable genotype, that is genotype 3 and 7. Genotype 8, 12, 15 specific at location B; genotype 9, 11, 14, 16 specific at location D and E; and genotype 1, 2, 4, 5, 6, 10 and 13 specific at location A and C.
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Judul: Pembuatan Film Tipis Cu2ZnSnS4 sebagai Lapisan Penyerap Cahaya pada Sel Surya Menggunakan Metode Elektrodeposisi
Abstrak: Thin film of Cu2ZnSnS4 (CZTS) is an alternative semiconductor used as light absorber layer on solar cell. CZTS can replace silicon that commonly used as commercial semiconductor. The advantage of using CZTS as absorber layer is due to the abundance of its chemical composer on earth, and its high value of absorption coefficient. The absorber layer was made by using electrodeposition method on ITO glass substrates. The films were deposited at room temperature using potentiostatic mode with a potential of –1.05 V for 30, 45, and 60 minutes. After that, the films were annealed at two different temperatures, 180 ºC and 500 °C, for 45 minutes in N2/H2S atmosphere. Based on X-ray diffraction analysis, the polycrystalline thin film obtained fall into kesterite crystal phase. This type of crystal was obtained when the CZTS was annealed at 500 °C in H2S/N2 atmosphere. The value of optical band gap energy for the CZTS thin film was 2.2 eV with the film thickness about 1.228–6.366 μm. The sample of CZTS with electrodeposition time of 45 minutes and annealing temperature of 500 °C showed the best result and in conformity with absorber layers criteria for solar cells.
Keyword: semiconductor, ITO glass, CZTS thin film, electrodeposition