Judul: Aplikasi Regression Tree pada Prestasi Siswa SMA ALAtiqiyah Sukabumi
Abstrak: Regression Tree (Regression Trees) is a non-parametric technique. This technique is used to explore the large and complex data. Complex dimensions can be formed large data, mixed data types, such as continuous and categorical, either nominal or ordinal. One application of regression tree is in the field of education, including to determine the factors that affect student’s achievement (academic ability) students that is the results of National Examination (UN). There are many factors influenced student’s achievement, those are internal and external factors. There are four factors that most influenced on student’s achievement, those are environment where the student lived, the average score of student’s report, final test, and gender.
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Judul: Identification of national education standards that influence the national exam with regression trees method
Abstrak: Pencapaian nilai Standar Nasional Pendidikan untuk Sekolah Menengah Atas di Pulau Jawa pada tahun 2013 menunjukkan adanya keragaman. Perbedaan ketercapaian Standar Nasional Pendidikan ini dapat memengaruhi nilai Ujian Nasional (UN). Hal yang dapat dilakukan untuk memaksimalkan pencapaian nilai UN adalah dengan mengklasifikasikan rata-rata nilai UN berdasarkan faktor-faktor yang berpengaruh terhadap nilai UN. Metode pohon regresi merupakan salah satu metode yang dapat digunakan untuk klasifikasi data dengan peubah respon berupa data numerik. Evaluasi kestabilan pohon optimum dilakukan dengan melakukan pengambilan contoh acak sebanyak tiga kali tanpa pengulangan. Pohon yang dihasilkan dari pengulangan tersebut berbeda-beda, hal ini menunjukkan ketidakstabilan. Penentuan peubah yang stabil dilakukan dengan random forest. Hasil dari random forest menunjukkan peubah yang stabil, diantaranya provinsi, Standar Sarana dan Prasarana, dan Standar Kompetensi Lulusan. Ketiga peubah tersebut merupakan peubah yang berkontribusi besar terhadap nilai UN. D.K.I Jakarta dan Jawa Timur perlu memperhatikan Standar Kompetensi Lulusan, sedangkan Banten, D.I Yogyakarta, Jawa Barat, dan Jawa Tengah perlu memperhatikan Standar Sarana dan Prasarana untuk mendapatkan nilai UN yang lebih baik., Achievement of The National Education Standard for high schools in Java Island in 2013 showed variation. The difference in the achievement of The National Education Standard can affect the student’s score in The National Exam (UN). A solution for maximizing UN is classifiying the student’s score of UN based on the factors that are associated with UN. Regression tree analysis method is one of the classification method which can be used for numerical response variable. Evaluation of stability of the optimum tree is done by resampling three times with no replacements. The trees obtained from the procedure showed differences which indicates instability. Therefore this method should be continued with random forest method to see which variables are stable. The stable explanatory variables based on random forest are provinces, Infrastructure Standards, and Competency Standards. These three variables are the variables that highly contribute to UN. D.K.I Jakarta and East Java should concern to improve Competency Standards, while Banten, D.I Yogyakarta, West Java and Centre Java should concern toimprove Infrastructure Standards to a the better score of UN. Keywords:regression trees, random forest, national standards of education
Keyword: pohon regresi, random forest, standar nasional pendidikan

Judul: Extraction and Characteristic of Collagen and Nanoparticle Collagen from the Skin of Stingray Fish (Pastinachus solocirostris) as Ingredient of Cosmetics.
Abstrak: Isolation of collagen from the skin of stingray fish (Pastinachus solocirostris) has been successfully conducted with three stages: first soaked in 0.05 M NaOH with a sample/solution ratio of 1:10 (w/v) for 6 hour, second soaked in 0.1 M acetic acid with a sample/solution ratio of 1:6 (w/v) for 2 hour, and third extraction with destilated water at temperature 40 C for 2 hour with a yield of 14.475 % (wet base). Nanoparticle collagen was made with desolvation method using etanol as a desolvating agent with a collagen solution/etanol ratio of 1:1. Yield of nanoparticle collagen was 9.64% (wet base) with particle size of 185.24 nm. Collagen and nanoparticle collagen is in the form of white powder with whiteness degree 72.48% and 60.03%, respectively. Protein is the major component in collagen and nanoparticle collagen (86.97% and 86.18%) with trace amount of ash (0.17% and 0.13%) and fat (0.19% and 0.25%), respectively. Based on sodium dodecyl sulfate-polyacrylamide gel electrophoresis patterns, amino acid composition, and fourier transform infrared (FTIR) spectra of both collagen and nanoparticle collagen were characterized as type I collagens. Nanostructural analysis of collagen and nanoparticle collagen by Scanning Electron Microscopy (SEM) shows that both were separate aggregates. Other characteristics of collagen and nanoparticle collagen were: Tmax of 165.88 C and 156.63 C; Viscosity 292.33 cP dan 110 cP; pH 5.00 dan 4.93; respectively. Collagen has highest solubility at pH 7 and the isoelectric point at pH 6, 9, and 10. Therefore, nanoparticle collagen has highest solubility at pH 3 dan and the isoelectric point at pH 6. Collagen and nanoparticle collagen from skin of stingray fish (Pastinachus solocirostris) has a characteristic for a potential use as a cosmetic ingredient.
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