Judul: Analisis Hoax Menggunakan Seleksi Fitur Chi Square dengan Relevance Feedback
Abstrak: Hoax merupakan informasi tidak benar dan berbahaya karena dapat merubah persepsi seseorang dengan menyampaikan informasi palsu sebagai kebenaran dan dapat mengurangi kredibilitas. Pembelajaran mesin dapat digunakan untuk menganalisa sebuah berita merupakan hoax atau non hoax. Penelitian ini bertujuan untuk mengklasifikasikan berita hoax menggunakan 600 dokumen berita yang terdiri dari 300 berita hoax dan 300 berita non hoax. Data latih dan data uji dibagi berdasarkan pengujian metode 10-fold cross validation lalu menggunakan seleksi fitur Chi Square yang akan dibandingkan dengan Inverse Document Frequency dengan klasifikasi Multinomial Naïve Bayes dan menggunakan Incremental Naïve Bayes untuk menghitung nilai Relevance Feedback. Penelitian ini menghasilkan nilai rata-rata akurasi yang cukup baik yaitu sebesar 94.5% untuk seleksi fitur Chi Square dan 83.5% untuk IDF. Setelah menggunakan Relevance Feedback rata-rata akurasi bertambah menjadi 97.5% untuk seleksi fitur Chi Square dan 97% untuk seleksi fitur Inverse Document Frequency.
Keyword: chi square, hoax, incremental naïve bayes, inverse document frequency, multinomial naïve bayes, relevance feedback

Judul: Metode Klasifikasi K-Nearest Neighbor untuk Analisis Hoax.
Abstrak: Hoax adalah informasi sesat dan berbahaya yang dapat menyesatkan persepsi manusia dengan menyampaikan informasi palsu sebagai kebenaran. Hoax mampu mempengaruhi banyak orang dengan menodai suatu citra dan kredibilitas. Salah satu cara dalam bidang Information Retrieval yang dapat digunakan untuk membedakan berita hoax dan non-hoax adalah dengan menggunakan metode klasifikasi teks. Metode klasifikasi yang akan digunakan pada penelitin ini adalah metode K-Nearest Neighbor dan dibandingkan dengan Multinomial Naive Bayes. Data pada penelitian ini berupa 300 dokumen hoax dan 300 dokumen non-hoax. Data dibagi menjadi 10 model pengujian menggunakan metode k-fold cross validation. Hasil akurasi tertinggi dari klasifikasi K-Nearest Neighbor sebesar 81.67% sedangkan Multinomial Naive Bayes menghasilkan akurasi tertinggi sebesar 93.33%. Hasil akurasi rata-rata dari klasifikasi K-Nearest Neighbor sebesar 77.50% dan Multinomial Naive Bayes sebesar 85.83%.
Keyword: hoax, klasifikasi, K-Nearest Neighbor, Multinomial Naive Bayes

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)