Judul: Klasifikasi Naive Bayes pada Data Tidak Seimbang untuk Kasus Prediksi Resiko Kredit Debitur Kartu Kredit.
Abstrak: Banking business in Indonesia is still dominated by the credit business field. Most of the bank's revenue comes from this business field. Unfortunately, credit risk can cause problems in loans which can reduce the bank’s revenue. This research uses a Naive Bayes classification analysis on the imbalanced data for the predictions of debtor’s credit risk that are able to classify the future debtor into the following two categories: good or bad. Sampling strategy is used to overcome the problems of imbalanced data. Duplication oversampling, random oversampling, random undersampling, and cluster undersampling are chosen as the methods. It is found that the random oversampling method shows the best value after sampling strategy is conducted with an f-measure of 83.30%.
Keyword: undersampling., oversampling, naive bayes classification, imbalanced data, Credit risk

Judul: Klasifikasi Debitur Kartu Kredit Menggunakan Algoritme K-Nearest Neighbor untuk Kasus Imbalanced Data
Abstrak: Data is said to suffer the class imbalanced problem when the class distribution are highly imbalance. In this case, minority class is more difficult to predict then the majority class. Though the minority class sometime has important information. In this paper, classification analysis of credit card debtors is conducted by using k-nearest neighbor that can classify debtors into two categories, good or bad. Analysis of a prospective debtor is essential to minimize credit risk. One approach taken to overcome imbalanced data problems is to modify instance distribution using oversampling and undersampling method. The evaluation is conducted by comparing the value of parameter k, accuracy, precision, recall, and F-measure. The evaluation results show that oversampling technique gives the best result of 96.24% with k = 3, 99.23% recall with k = 2, 95.21% precision with k = 1, and 96.30% F-measure with k = 3.
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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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