Judul: Analisis Diskriminan Logistik untuk Klasifikasi Sekolah Standar Internasional Berdasarkan Status Afiliasi
Abstrak: Affiliate program is one of the government's program to improve the quality of education in Indonesia. The main activity in this program is a partnership with schools in developed countries so that interactions can occur between the components of the school. Implementation of this program need support of the government and society. In order that all support can be utilized maximally, required methods to classify and predict an affiliation status of school. Logistic discriminant analysis is one of the alternatif method to classify which the variables is a combination of numerical and categorical. Logistic discriminant function that used to classify of schools into the particular affiliate status is obtained by logit model predicted as a result of final reduction models.. Through the partial parameter testing, variables that affect the status of affiliation is school type, education of headmaster, and amount of the monthly tuition of international class. The classification accuracy of the discriminant function that is equal to 66.46%.
Keyword: affiliate, logistic discriminant analysis

Judul: Perbandingan regresi logistik biner dengan jaringan syaraf tiruan (studi pada klasifikasi status akreditasi Sekolah Menengah Pertama Provinsi DKI Jakarta)
Abstrak: Classification is one of statistical technique in classifying data compiled systematically. One popular example of classification in the field of education is the accreditation status of the school. Accreditation status of schools affected by the standard of Teachers and Education Personnel (TOD). There are many statistical methods that can be used to solve classification problems, including binary logistic regression and Artificial Neural Network (ANN). The result of the calculations in studies using binary logistic regression gives an Area Under Curve (AUC) of 0.852 for training data and 0.834 for testing data. Calculation with a back propagation ANN for training data and testing data give an AUC of 0.911 and 0.899. Thus, the back propagation ANN can predict better than the binary logistic regression. The variables that significantly affect the classification of the accreditation status of the school is the number of teachers (X1) and the qualifications of chief administrative personnel (X6).
Keyword: Bogor Agricultural University (IPB), binary logistic regression., neural network, classification, back propagation

Judul: Synthesis of Apatite - Chitosan Composite Using Duck Eggshell and Chitosan with Temperature and pH Control
Abstrak: Composite of apatite-chitosan was prepared by using chitosan as polymer matrix. Calcium phosphate was prepared from CaO and (NH4)2HPO4, which the ratio Ca : P had to be 1.67. Chitosan is produced by deacetilase from biopolymer chitin. Duck eggshell (95% CaCO3) as starting material was converted to be calcium oxide (CaO) through calcinations with temperature 1000oC for 5 hours. In-situ and ex-situ methods were prepared from apatite and chitosan (dissolved with acetate acid 2%). Calcium phosphate prepared for bone implantation, but it is too fragile and brittle to be implant into the body. So addition of chitosan can decrease crystalinity and increase mechanic characteristic (tougher). Composite apatite-chitosan was resulted by fast precipitation. Fast precipitation was held in a breaker glass with nitrogen atmosphere, under controlled temperature at 37oC and pH 7, in order to increase amount of hydroxyapatite. Precipitation with CaO which was dropped by (NH4)2HPO4. Hydroxyapatite and chitosan were appearing at samples with in-situ and ex-situ methods which indicating by peak matching of XRD (closed lattice parameter, crystal size), overlapping at FTIR spectra and supporting by SEM picture (homogenous and agglomerated particle). However, it still needs further research to examine biocompatibility osteoconductive degree of sample by in-vivo and in-vitro test.
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