Judul: Klasifikasi Dokumen Teks Menggunakan Metode Support Vector Machine dengan Pemilihan Fitur Chi-Square.
Abstrak: Increasing number of documents makes people more difficult to obtain the information which they desired. This problem requires text processing techniques to organize the documents in accordance with the categories. One of which is text classification. Text classification can organize document in accordance with predefined categories automatically (supervised machine learning). One popular method of text classification is support vector machines (SVM) that tries to find the best hyperplane in the input space. This algorithm is the best classification algorithm compared with other vector space classification method, namely Rocchio, k-nearest neighbor (KNN) and decision tree. This research measures the suitability of SVM for text classification and to prove whether the SVM is able to classify the documents in a linear separable manner. The final result shows that linear kernel and polynomial kernel in the SVM test produce the same accuracy value of 96.3504% and testing the RBF kernel produces accuracy of 95.6204% for classification of text documents using chi-squared feature selection
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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: Nisbah Kelamin Ikan Pelangi Iriatherina Werneri Pada Perbedaan Suhu Pemeliharaan
Abstrak: Ikan pelangi Iriatherina werneri merupakan ikan hias air tawar dari famili Melanotaenidae (Rainbowfishes) yang ditemukan di Papua. Ikan pelangi (Iriatherina werneri) jantan memiliki warna dan bentuk sirip yang indah, serta bernilai ekonomi lebih tinggi dibandingkan ikan betina. Penelitian ini dilakukan untuk mengevaluasi pengaruh perbedaan suhu pemeliharaan terhadap nisbah kelamin ikan pelangi Iriatherina werneri dalam wadah budidaya, kelangsungan hidup, derajat penetasan dan pertumbuhannya. Penelitian menggunakan Rancangan Acak Lengkap dengan perlakuan suhu (28-30 ºC, 30-32 ºC, dan suhu ruang) masing-masing dengan 5 ulangan. Perlakuan suhu diberikan mulai dari fase telur sampai 60 hari pemeliharaan. Hasil penelitian menunjukkan suhu mempengaruhi nisbah kelamin pada ikan pelangi (P<0,05). Persentase jantan pada perlakuan suhu 30-32 ºC lebih tinggi, yaitu 73,3% dibandingkan dengan perlakuan suhu 28-30 ºC sebesar 56,7%, sedangkan pada perlakuan suhu ruang menghasilkan 30% ikan jantan. Pada perlakuan suhu 28-30 ºC dan 30-32 ºC menghasilkan persentase ikan jantan dua kali lipat lebih tinggi yaitu sebesar 56,7% dan 73,3% dibandingkan dengan pemeliharaan pada suhu ruang sebesar 30%. Kelangsungan hidup pada penelitian ini berkisar antara 23,9% sampai 40,3%, derajat penetasan berkisar antara 43,4% sampai 47,2% dan pertumbuhan ikan pelangi pada perlakuan pemeliharaan dengan suhu 28-30 ºC menunjukkan kecenderungan pertumbuhan yang lebih tinggi dibanding perlakuan suhu 30-32 ºC dan suhu ruang, yaitu mencapai 23,4 mm.
Keyword: Iriatherina werneri, jantan, suhu, nisbah kelamin