Judul: Metagenome Classification Using Naïve Bayes Classifier Method.
Abstrak: Metagenome study is an important step in the taxonomic grouping. Grouping can be conducted using binning method. Binning is required to determine contigs of each phylogenetic species groups. In this study, binning is done using supervised learning based composition approach. We used NaïveBayes Classifier method for performing supervised learning and employed counting of k-mer frequencies for extracting feature. The classification process was conducted at genus-level taxon. The results showed that using short fragments (400 bp), our method could obtain the accuracy of 49.34 % and 53.95 % with features of 3-mers dan 4-mers frequencies, respectively. Meanwhile, the accuracy of our method was significally increased when classifying long fragments (10 kbp). Our method could obtain the accuracy of 82.23% with 3-mers frequencies feature and 85.89% with 4-mers frequencies feature. It can be concluded that the accuracy of our classifier was increased by increasing the size of fragments. Moreover, in this research, the 4- mers frequencies feature gave the best results for classifying metagenome fragments.
Keyword: metagenome, k-mers, Naïve Bayes Classifier, binning

Judul: Perbandingan Ekstraksi Ciri K-Mers dan Spaced K-Mers pada Klasifikasi Fragmen Metagenome dengan Naïve Bayes Classifier
Abstrak: Metagenome is a genetic material obtained from a simple which is taken directly from the environment such as soil, marine, or human entrails. These metagenome fragments contain a variety of organism , so that a binning process required to classify them before conducting genome assembly. This research employs naïve Bayes classifier (NBC) and spaced k-mers as a feature extraction to classify these fragments into genus level. The results will be compared to those of method which uses NBC and k-mers feature extraction. K-mers feature is a common feature in the DNA fragments classification problem. The comparison results show that the accuracy of classifier using NBC and spaced k-mers is higher than that of classifier using NBC and k-mers.
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Judul: Pengaruh tekanan operasi terhadap karakteristik curahan air dan erosi percikan yang dihasilkan oleh orbitor sprinkler
Abstrak: Irigasi curah (sprinkler irrigation) merupakan sistem irigasi yang diusahakan sedemikian rupa sehingga pemberian air untuk kebutuhan pertumbuhan tanaman menyerupai keadaan hujan dan biasa disebut dengan overhead irrigation. Karena sistem irigasi ini dibuat menyerupai hujan, maka ada beberapa hal penting yang perlu diperhatikan, karena hujan atau butiran air yang jatuh ke permukaan tanah dengan kecepatan dan jumlah tertentu dapat menyebabkan terjadinya kerusakan tanah atau erosi. Erosi adalah salah satu bentuk kerusakan tanah sebagai akibat hilangnya lapisan atas/lapisan olah tanah (top soil). Kehilangan ini disebabkan oleh proses penghancuran dan pengangkutan lapisan olah tanah dari suatu tempat ke tempat lain oleh media atau kekuatan alam seperti air, angin atau gaya gravitasi. Masalah khusus ini bertujuan untuk mempelajari pengaruh tekanan operasi terhadap karakteristik curahan air yang dihasilkan oleh Orbitor Sprinkler dan pengaruhnya terhadap kerusakan tanah, khususnya erosi percikan. Dari hasil pengukuran didapat bahwa karakteristik curahan air yang dihasilkan oleh nosel dalam pengoperasian ..dst
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