Judul: An Application of Genetic Algorithm for Clustering Observations with Incomplete Data
Abstrak: Cluster analysis is a method to classify observations into several clusters. A common strategy for clustering the observations uses distance as a similarity index. However distance approach cannot be applied when data is not complete. Genetic Algorithm is applied by involving variance (GACV) in order to solve this problem. This study employed GACV on Iris data that was introduced by Sir Ronald Fisher. Clustering the incomplete data was implemented on data which was produced by deleting some values of Iris data. The algorithm was developed under R 3.0.2 software and got satisfying result for clustering complete data with 95.99% sensitivity and 98% consistency. GACV could be applied to cluster observations with missing value without any pre-processing step to incomplete observations. Performance on clustering observations with incomplete data is also satisfying but tends to decrease as the proportion of incomplete values increases. The proportion of incomplete values should be less than or equal to 40% to get sensitivity and consistency not less than 90%.
Keyword: Incomplete Data, Genetic Algorithm, Cluster Analysis

Judul: Kajian Analisis Regresi Linier Bergerombol dengan Pendekatan Algoritma Genetika
Abstrak: Clustered Linear Regression (CLR) analysis with Genetic Algorithms (GA) approach is able to find solutions to the data clustering based on the adjusted Rsquare (R2 adj) value, but have not been able to determine the optimum clusters because of the larger number of clusters the R2 adj value also higher. This analysis is able to determine cluster for an observation so that it can improve the ability of linear regression analysis. If compared to classical linear regression analysis, this analysis is able to produce better estimation of parameters and R2 adj value. CLR analysis with GA approach program can be accessed at http://bit.ly/CLRwGA
Keyword: Bogor Agricultural University (IPB), genetic algorithms, clustered linear regression

Judul: Sintesis dan Karakterisasi Membran Penukar Proton Polistirena Tersulfonasi sebagai Bahan Perangkat Direct Methanol Fuel Cell
Abstrak: Sulfonated polystyrene can be used as proton exchange membrane (PEM). Characterization and performance of PEM has been performed on sulfonated polystyrene (PSS) using fourier transform infrared spectrophotometer, scanning electrone microscope, and degree of sulfonation (DS) parameter. The success of the process indicated by the DS of the membrane PSS 3%, 5%, and 10% were 35.09%; 42,26%; and 48.15%, respectively. The infrared spectrum shows that sulfonation has been succesful in 10% PSS membranes as indicated by the presence of sulfonate groups (-SO3) at wavenumber 1029.39 and 1178.03 cm-1. PSS membrane surface morphology is categorized non-porouse. Methanol permeability with qualitative test showed that the membrane PSS 3%, 5%, and 10% have no infiltration. The results of measurements of the conductivity (σ) obtained by PS, PSS 3%, PSS 5%, and PSS 10% were (0.0114; 1.5511; 3.0919; and 3.8949) × 10-6 S/cm, respectively. So that the membrane PSS 3%, 5%, and 10% can be used as a device in direct methanol fuel cell.
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