Judul: Text Feature Weighting for Summarization of Document Bahasa Indonesia Using Genetic Algorithm.
Abstrak: This thesis aims to perform text feature weighting for summarization of document bahasa Indonesia using genetic algorithm. There are eleven text features, i.e, sentence position (f1), positive keywords in sentence (f2), negative keywords in sentence (f3), sentence centrality (f4), sentence resemblance to the title (f5), sentence inclusion of name entity (f6), sentence inclusion of numerical data (f7), sentence relative length (f8), bushy path of the node (f9), summation of similarities for each node (f10), and latent semantic feature (f11). We investigate the effect of the first ten sentence features on the summarization task. Then, we use latent semantic feature to increase the accuracy. All feature score functions are used to train a genetic algorithm model to obtain a suitable combination of feature weights. Evaluation of text summarization uses F-measure. The F-measure directly related to the compression rate. The results showed that adding f11 increases the F-measure by 3.26% and 1.55% for compression ratio of 10% and 30%, respectively. On the other hand, it decreases the F-measure by 0.58% for compression ratio of 20%. Analysis of text feature weight showed that only using f2, f4, f5, and f11 can deliver a similar performance using all eleven features.
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Judul: Peringkasan Teks Bahasa Indonesia dengan Pemilihan Fitur C4.5 dan Klasifikasi Naive Bayes
Abstrak: This research summarized Indonesian text documents using naive bayes (NB) classification method. Segmentation of the documents into sentences and feature computation are the initial stages of training the system to determine which sentences are classified as summary. The classification used 11 features (f1-f11). The features are selected using C4.5 decision tree to determine the features that affect the summary, reduce the number of features and speed up the summarization. The accuracy of summarization using 10 features (f1-f10) was 34.63%, 37.96%, and 28.14% for compression rate (CR) of 10%, 20%, and 30%, respectively. Adding f11 and C4.5 produced an accuracy of 52.45%, 51.49% and 51.35% for CR 10%, 20%, and 30%, respectively. Text summarization using NB classification, C4.5 feature selection, and additional f11 feature produced better accuracy and faster summarization.
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Judul: Enteric Collibacillosis Pada Anak Babi Baru Lahir: Patogenesa dan Perubahan-Perubahan Patologisnya
Abstrak: Diare disebabkan oleh infeksi bakteri Escherichia coli pada anak-anak babi baru lahir yang peka terhadap en terotoksin produk bakteri tersebut. Dikenal sebagai colibacillosis. Patogenesa dari colibacillosis anak babi baru lahir adalah (1) infeksi oleh E. coli patogen, (2) proliferasi E. coli di lumen usus halus, (3) produksi dan pelepasan enterotoksin, dan (4) aktifitas toksin pada usus halus. Dalam proses proliferasi, adanya antigen pili K88 sangat penting karena memungkinkan bakteri perlekatan dengan epitel mucosa usus halus. mengadakan Setelah ko lonisasi dan proliferasi segera toksin dilepaskan. Akti- fitas toksin menginduksi sekresi yang berlebihan dari u- sus sehingga banyak cairan yang dikeluarkan ke lumen usus. Hal ini mengakibatkan banyak cairan dan elektrolit hilang sehingga timbul diare, dehidrasi dan asidosis yang sering menyebabkan kematian. Perubahan-perubahan patologis yang umum adalah dis tensi usus halus, dilatasi lambung dan infark pada kurva- tura mayor. Perubahan-perubahan histologis yang terjadi adalah enteritis hemorrhagica acuta, oedem dan kongesti pembuluh darah di lamina propria, akumulassi leukosit inti polimorf, sel monosit, dan inti sel mengalami piknosis Thrombus pada vena dan degenerasi serta desquamasi sel epitel usus….
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