Judul: Klasifikasi artikel berita menggunakan metode naive Bayes classifier
Abstrak: Banyaknya artikel berita yang diterbitkan membuat pengelompokkan berita sulit dilakukan dan rentan kesalahan. Salah satu cara untuk mempermudah pengelompokan adalah menggunakan model klasifikasi. Tujuan penelitian ini adalah menerapkan 2 teknik klasifikasi naïve Bayes, yaitu multinomial dan Bernoulli untuk klasifikasi dokumen berbahasa Inggris dari korpus Reuters- 21578, serta melakukan perbandingan antara klasifikasi 2 kelas dan 6 kelas. Hasil penelitian menunjukkan bahwa pada metode klasifikasi multinomial maïve Bayes dengan menggunakan metode seleksi fitur chi-square mendapatkan akurasi sebesar 92.81% pada klasifikasi 2 kelas dan 92.73% pada klasifikasi 6 kelas. Model klasifikasi Bernoulli naïve Bayes mendapatkan pula akurasi 92.57% untuk klasifikasi 2 kelas dan 85.94% untuk klasifikasi 6 kelas. Penelitian ini juga membandingkan akurasi klasifikasi untuk kosa kata yang dihasilkan menggunakan derajat bebas 1 dan 5 pada seleksi fitur chi-square.
Keyword: bernoulli, chi-square, classification, multinomial, naive bayes, Model klasifikasi, Pembuangan stop words

Judul: Klasifikasi Dokumen Berita Menggunakan Metode Support Vector Machine dengan Kernel Radial Basis Function
Abstrak: Every day the number of text documents, especially online news documents increase. As a result, it is more difficult for information seekers in obtaining the desired information. This problem requires a text processing technique that is able to automatically classify text documents based on predetermined categories. This technique is document classification. A very good and popular classification method is support vector machine (SVM). SVM tries to find the best hyperplane which separates 2 classes of data in a vector space. By applying kernel trick, SVM can implement classification in non-linear case. The goals of this research are applying the radial basis function kernel of SVM to classify Reuters-21578 news documents, and comparing the weighting method term frequency (tf) and term frequency-inverse document frequency (tf-idf). The research uses chi-square in feature selection, producing 1716 features out of 7279 terms from tokenization and stopwords removal. The final result shows that the SVM classification produces an accuracy of 93.21% using tf weighting and 92.97% using tf-idf weighting
Keyword: Bogor Agricultural University (IPB), support vector machine, radial basis function, feature selection, document classification, chi-square

Judul: Drought Stress Tolerance Mechanisms of Eggplant (Solanum spp.): Physiology and Molecular.
Abstrak: Eggplant (Solanum melongena L.) is a popular and economically important vegetable crop grown in the tropics and subtropics, especially in Asia and Africa. Most of these crops grown in Asia and Africa are tolerant to biotic and abiotic stresses. Eggplant has a wide variation in morphological and physiological characteristics, therefore, it is necessary to explore the germplasm to gain more genotypes tolerant to biotic and abiotic stresses. Sufficient water availability at the first stage of plant growth is very important. Limited water supply may lead to drought stress. The long period of drought stress may disturb the metabolic process and lead the irreversible damage of the plant tissues, so the plant can not recover. This abiotic stress has been significantly proved to be one of factors decreasing the plant growth and productivity. The objective of this research was to reveal physiological and molecular response of six eggplant accessions (i.e. 098, 155, 414, 754, 772, and 827 accessions, and Panjalu-F1 as the control genotype) to drought stress. Plants were grown in medium containing soil, sand and compost (1:1:1, v/v/v) in the greenhouse. Plants were exposed to the drought treatment at 21 days after the plants have 6 fully leaves. Some parameters were examined during the drought treatment, which were media water content (MWC), relative water content (RWC), plant growth and dry weight, proline concentration, chlorophyll content and polyamine concentration. Total RNA was extracted from leaves on day 21st of the treatment. The arginine decarboxylase S. melongena (SmADC) fragment gene was amplified from the cDNA. ADC gene is one of genes involved in polyamine biosynthesis and plays important role in the plant tolerance mechanism to drought stress. The results showed that drought stress significantly reduced plant height, leaf area, stomatal density and aperture in all plants. Levels of chlorophylls were similar during the drought treatment in all plants. Proline and/or polyamines were accumulated and reached the maximum levels after 14 to 21 days after the treatment. High levels of these amines can be used to indicate that the plant is stressed by drought. Levels of proline and polyamines, especially putrescine, increased 10 times higher in the stressed-plants compared to those grown in the optimum condition. cDNA was synthesized from the total RNA by reverse transcription. In total, four fragments of SmADC were obtained by PCR from cDNA of accession 098 (2 fragments), cDNA of accession 772 (1 fragment) and genomic DNA of accession 098 (1 fragment). ADC primers were designed based on the conserved regions in ADC Solanum lycopersicum (accession number HM629957.1). Sequences analysis showed that the four SmADC fragments were 1 442 bp, 1 422 bp, 1 407 bp and 636 bp, encoding 151, 357, 466, 182 amino acids, respectively. Nucleotide alignment analysis showed that four SmADC fragments were 86-93 % homologue to Solanum lycopersicum (Acc: NM_001247720.1), Datura stramonium (Acc: AJ251898.1), Capsicum annuum (Acc: AY156514.1) and Nicotiana tabacum (Acc: AF321137.1). Based on the phylogenetic tree developed from the deduced amino acid sequence of ADC, SmADCs were grouped with Solanum lycopersicum, Datura stramonium, Capsicum annuum and Nicotiana tabacum. Analysis of conserved domains revealed that
Keyword: eggplant, proline, polyamine, arginine decarboxylase (ADC), pyridoxal 5-phosphate (PLP)