Judul: Perbandingan Metode Seleksi Fitur pada Spam Filter Menggunakan Klasifikasi Multinomial Naïve Bayes
Abstrak: Nowadays lots of unwanted email called spam may freely get into the inbox entry. Therefore spam filter software made to classify spam and non-spam email (ham) automatically. Naïve Bayes frequently used today as classification method for it simple and easy to be implemented. Naïve bayes has a good performance to classify multinomial document compared to multivariate Bernoulli when it comes to large vocabulary. Feature selection needed to improve classification model accuracy and make computation process more efficient. There are three feature selection methods used such as inverse document frequency (IDF), mutual information (MI), and chi-square. Based on accuracy level, the result of this study shows that MI is the best feature selection method with 93.77% accuracy and 9507 vocabulary as an identifier
Keyword: Bogor Agricultural University (IPB), spam filter, multinomial Naïve Bayes, feature selection

Judul: Spam Filter Menggunakan Model Klasifikasi Multivariate Bernoulli dan Multinomial Naïve Bayes
Abstrak: Pertumbuhan pengguna email memicu peningkatan spam email sehingga diperlukan teknik spam filter. Model klasifikasi Naïve Bayes (NB) adalah salah satu metode supervised learning yang dapat digunakan untuk spam filter karena tingkat akurasi yang tinggi dan mudah diimplementasikan. Multivariat Bernoulli NB menggunakan atribut Boolean sedangkan Multinomial NB menggunakan frekuensi term, adalah dua model NB yang sering digunakan untuk fungsi klasifikasi. Pemilihan fitur ciri yang baik juga berpengaruh pada peningkatan akurasi klasifikasi. Penelitian ini mencoba memodelkan spam filter menggunakan model klasifikasi Multivariat Bernoulli dan Multinomial NB kemudian membandingkan akurasinya. Seleksi fitur chi-square dipilih dengan harapan dapat menghasilkan fitur ciri yang lebih baik. Model Multinomial NB tanpa seleksi fitur menghasilkan akurasi tertinggi sebesar 95.31%, sedangkan untuk tingkat akurasi terendah didapatkan pada model Multivariate Bernoulli tanpa seleksi fitur sebesar 89.69%. Seleksi fitur chi-square meningkatkan akurasi model Multivariate Bernoulli sebesar 3.31%, sedangkan Multinomial NB mengalami penurunan akurasi sebesar 1.98%.
Keyword: multinomial, multivariat bernoulli

Judul: Characterizations of low alloy steel sae 4422  plated with chromic acid (Cro3)
Abstrak: Characterizations of low alloy steel SAE 4422 plated with chromic acid (CrOrO3) was use Optical Microscopy (OM), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), RD),Energy Dispersive Analysis of X-Ray (EDAX), Hardness Test and Roughness Test. Microstructures analysis exhibits cracks and grain boundaries microcracks as a characteristics of chrome metal found at plating metal. Perlite and Ferrite as grains of steel found at base metal with grain boundaries around it. Phase analysis of plating metal appropriate to chrome metal with lattice constant (a) is 2.559 Å and phase analysis of base metal appropriate to iron ferrite with lattice constant (a) is 3.318 Å. Both plating and base metal have cubic system. Chemical analysis of plating metal at surface section exhibits that cracks area have highest value of carbon element compare with grains and grains boundaries area. While chemical analysis of base metal at cross section exhibits that perlite have highest value of carbon element compare with ferrite and grain boundaries. The hardness value of plating metal at surface section and cross section are 753 and 637 VHN. While, the hardness value of base metal and interface area at cross section are 205 and 373 VHN. The roughness value at measurement points of chrome surface for as received sample are 0.445 μm. Observation used Optical Microscopy and Scanning Electron Microscopy exhibits surface irregularities combine to form surface texture of plating metal at surface section.
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