Judul: Pendugaan Parameter Model Regresi Linier Berganda Berbasis Pencilan Sel Menggunakan Metode Detecting Deviating Cells
Abstrak: Salah satu proses dalam pemodelan regresi adalah pendugaan parameter. Pendugaan parameter umumnya menggunakan metode ordinary least squares (OLS). Akan tetapi, metode ini kurang baik saat digunakan terhadap data yang mengandung pencilan. Pencilan umumnya mengacu pada pencilan baris (rowwise outliers) dan pencilan sel (cellwise outliers). Pencilan baris menangani dengan menghapus suatu baris data jika pada baris tersebut terdapat pencilan. Sementara pencilan sel menanganai pencilan hanya pada data yang terdeteksi pencilan saja tanpa menghapus baris data. Metode untuk menanganai data dengan memakai prinsip pencilan sel adalah metode detecting deviating cells (DDC). Tujuan dari penelitian adalah menganalisis pengaruh pencilan sel terhadap pendugaan parameter model regresi. Hasil analisis menunjukkan bahwa pendugaan parameter regresi pada data yang tidak mengandung pencilan tidak memiliki perbedaan baik menggunakan OLS saja ataupun dengan DDC. Namun jika data mengandung pencilan, metode OLS dengan DDC lebih unggul dibandingkan dengan OLS tanpa DDC. Hal ini didukung oleh hasil perbandingan nilai Mean Square Error pada OLS dengan DDC lebih kecil dibandingkan OLS serta R2 dan R2adj, One of the processes in regression modeling is parameter estimation. Parameter estimation generally uses the ordinary least squares (OLS) method. However, this method is not good when used with data containing outliers. Outliers generally refer to rowwise outliers and cellwise outliers. Row outliers handle by deleting a row of data if there are outliers in that row. While cell outliers handle outliers only on data detected by outliers without deleting rows of data. The method for handling data using the principle of cell outliers is the detecting deviating cells (DDC) method. The purpose of the study was to analyze the effect of cell outliers on estimating regression model parameters. The results of the analysis showed that the estimation of regression parameters in data that did not contain outliers had no difference either using OLS alone or with DDC. However if the data contains outliers, the OLS method with DDC is superior to OLS without DDC. This is supported by the comparison of the Mean Square Error value in OLS with DDC smaller than OLS and R2 and R2adj closer to 1.
Keyword: detecting deviating cell, ordinary least squares, pencilan

Judul: Metode Least Median of Squares (LMS) pada Analisis Regresi dengan Pencilan
Abstrak: Metode yang umum digunakan untuk menduga parameter dalam analisis regresi adalah Ordinary Least Squares (OLS) karena memiliki perhitungan yang sederhana. Namun, ketika data memiliki pencilan, metode ini menghasilkan dugaan parameter yang berbias. Karena itu disusunlah metode regresi kekar untuk mengatasi pencilan. Salah satu metode dalam regresi kekar adalah Least Median of Squares (LMS). Metode ini mampu mengatasi pencilan sehingga dihasilkan dugaan yang tak bias. Pada penelitian ini ingin diketahui persentase banyaknya pencilan yang mampu diatasi oleh LMS. Model yang digunakan dalam penelitian ini adalah model regresi linier sederhana. Data yang digunakan merupakan data hasil simulasi, dengan β0 dan β1 sebesar 5 dan 10. Nilai X berkisar antara 1-30. Untuk setiap nilai X akan diberikan satu nilai Y. Sisaan yang digunakan berasal dari sebaran Normal dengan μ= 0 dan σ2=3 yang nilai mutlak dari sisaan bakunya tidak lebih dari 2. Ukuran data yang digunakan adalah 30 amatan, 60 amatan, 90 amatan, 120 amatan, dan 150 amatan. Setiap ukuran data diberikan pencilan sebesar 0% (tanpa pencilan) , 5%, 10%, 15%, dan 20% pada peubah tak bebas Y dan diulang sebanyak 30 kali sehingga diperoleh 750 gugus data yang terbagi menjadi 25 subkelompok gugus data. Parameter regresi diduga dengan metode OLS dan LMS. Hasil dugaan parameter masing – masing metode pada setiap subkelompok gugus data diuji dengan metode Pitman’s Measure of Closeness untuk mengetahui metode mana yang lebih baik. Metode LMS lebih baik daripada metode OLS dalam menduga parameter regresi pada data yang memiliki pencilan hingga persentase pencilan 20% untuk pencilan sebesar 4 × σ2. Metode LMS lebih kekar dalam menduga parameter β1 daripada parameter β0. Semakin besar ukuran data, kekekaran LMS semakin menurun terutama dalam pendugaan β0.
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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