Judul: Eksplorasi Metode Penentuan Nilai End Point pada Algoritma Voting Feature Intervals 5
Abstrak: Voting Feature Intervals 5 adalah salah satu algoritma klasifikasi yang merepresentasikan deskripsi sebuah konsep oleh sekumpulan interval nilai-nilai feature (Güvenir 1998). Klasifikasi menggunakan algoritma ini didasarkan pada vote dari nilai-nilai pada feature. Cara kerja algoritma ini yaitu membuat interval dari setiap feature menggunakan instance yang terdapat pada feature tersebut. Interval yang dibuat dapat berupa range interval atau point interval. Point interval terdiri dari seluruh end point semua feature secara berurut sedangkan range interval terdiri dari nilai-nilai antara dua end point yang berdekatan namun tidak termasuk kedua end point tersebut. Nilai vote setiap kelas akan disimpan pada setiap interval. Tujuan dari penelitian ini adalah untuk mengeksplorasi metode penentuan nilai end point pada algortima VFI5. Pengeksplorasian nilai end point pada algoritma VFI5 dilakukan dengan cara menempatkan kembali end point yang lebih merepresentasikan batas setiap kelas. Penempatan end point itu dilakukan dengan berbagai cara, antara lain : metode desil dan metode min(n+1) max(n-1).
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Judul: Pemilihan Data Training untuk Meningkatkan Kinerja Voting Feature Interval 5 (VFI 5)
Abstrak: Voting Feature Interval 5 (VFI 5) is a supervised algorithm and an inductive learning algorithm for inducing knowledge classification from training information. VFI 5 algorithm is capable of classifying sample very well and can provide an explanation why and how the class groups of new samples from the classification can be predicted in the individual vote that each feature has been assigned to the class. VFI 5 algorithm determines the point interval for the classification process. Point interval is obtained by taking the lowest and the highest value of the sample in each class. In the testing process, if the test data are outside the sample interval they will have zero voting value and will reduce the accuracy of the classification results. The selection of training data with non-random sampling method uses the purposive sampling technique. The selection process is done by taking a few of the lowest and the highest feature values from each feature data to be training data. The remaining data which are not used as training data will be used as testing data. The propotion of training and testing data is 2:1. Among the three data used in the VFI 5 algorithm with the selection training data using the lowest and highest feature values, the iris data produced an accuracy of 98.04%, the accuracy of wines data is 96.56% and the acuracy of gender koi data is very high reaching 100%. The result of this study shows that the algorithm VFI 5 data selection method using the lowest and the highest feature values can improve the performance of the algorithm VFI 5.
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Judul: Extracellular Expression of thermostable Geobacillus stearothermophilus T1.2RQ Lipase for Biodiesel Production
Abstrak: The extracellular expression of enzymes in an excellent secretion host such as Bacillus subtilis is a useful strategy for making enzymes of industrial significance more affordable by lowering the cost of its downstream processing. Lipases are a category of hydrolases that catalyze the hydrolysis of triglycerides to glycerol and free fatty acids. Also, lipases catalyze the hydrolysis and transesterification of other esters as well as the synthesis of esters. They can perform very specific biotransformation reactions and are widely used in food, organic synthesis, detergents, cosmetic, and pharmaceutical industries. Geobacillus stearothermophilus T1.2RQ lipase is an industrially-desired thermostable lipolytic enzyme with an excellent hydrolytic and transesterification activity. This study aimed to express T1.2RQ lipase, in B. subtilis WB800 and ensure its secretion into the extracellular medium. Three signal peptides (AmyQ, Epr, LipA) and two promoters (Pgrac01 and Pgrac100) were used in the secretory-expression of T1.2RQ lipase, based on five constructed expression vectors constructed by restriction cloning and PCR mutagenesis. Sangers sequencing was used to verify constructs to ensure they are in the correct reading frame. Recombinants vectors, pHT43 (plasmid control), pHT43-T1.2RQ, pHT43- T1.2RQ_AmyQ, pHT43-T1.2RQ_Epr, and pHT43-T1.2RQ_LipA, were transformed by electroporation into Bacillus subtilis WB800. The electroporation was successful with the optimum condition of 2500V, 200 ohms, 25µF, and 5milliseconds. Recombinant B. subtilis pHT43 (negative control) and pHT43-T1.2RQlip + signal peptides were streaked on the lipidic agar, LA+TBN. All four recombinants, including the negative control (B. subtilis WB800-pHT43), produced clear zones on the TBN agar plate after overnight incubation (fig 2), indicating the presence of a lipolytic enzyme in all of the recombinant B. subtilis cells. pHT43-T1.2RQlip + signal peptides (AmyQ, Epr, and LipA) have clear zones with significantly higher diameters than B. subtilis WB800-pHT43 (negative control). This phenomenon suggests that the recombinant thermostable lipase T1.2RQ introduced into these cells was successfully expressed, thereby increasing the lipolytic capability of its host cells T1.2RQ lipase was expressed in 50ml terrific broth medium (TB) and the expression induced with 1mM IPTG. Lipase activity assay using p-nitrophenyl esters showed that all three signal peptides directed the secretion of T1.2RQ lipase into the extracellular medium. Signal peptide, LipA, resulted in the highest extracellular activity of 5.6 U/mL, which corresponds to a 6-fold increase over the parent B. subtilis WB800 strain. Meanwhile, signal peptides, AmyQ and Epr produced 4.2 U/mL and 3.4 U/mL activity respectively. SDS-Zymogram analysis confirmed that T1.2RQ lipase was correctly processed and secreted in its original size of 44 kDa. An attempt to further increase lipase expression level by promoter optimization showed that, contrary to expectation, promoter Pgrac100 exhibited similar expression levels as the original Pgrac01. Nevertheless, the demonstration of the successful secretion of T1.2RQ lipase in this work confirms the latter as a promising approach for the industrial production of the enzyme
Keyword: Bacillus subtilis, Expression, Extracellular, Heterologous, Lipase, Thermostable