Judul: Text Document Classification with Minor Component Analysis.
Abstrak: Document classification can improve information retrieval process by decreasing the search time and increase the relevance of the results. Many classification algorithms have been developed, e.g., Naïve Bayes Classifier, Nearest Neighbor, Principal Component Analysis, and Minor Component Analysis (MCA). This research investigates the performance of MCA in classifying text documents in Bahasa Indonesia. MCA has been applied for image classification, but has not been widely used in text classification. The dataset used in this research contains 750 documents from Media Indonesia Online, consisting of five classes, i.e., economics, education, crime, environment, and badminton. This research also observes the influence of stemming and stoplist in preprocessing to the classification performance. The experiment results show that MCA achieves more 90% accuracy and the preprocessing methods do not have significant effect to the performance. Keywords: document text classification, minor component analysis.
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Judul: Klasifikasi Dokumen Bahasa Indonesia Menggunakan Adaptive Classifier Combination (ACC)
Abstrak: Search engine is a tool to find an information that match with user’s request based on query or keywords. However, the query of search engine often shows irrelevance sites that didn’t match with user’s desire. Classification was developed to focused user’s request on the information that they searched, so the result would be more accurate and less effort yet effective and efficient for the system. Adaptive Classifier Combination is one of many methods that can be used for text classification. This method is a combination between k-nearest neighbor classification and Naive Bayes classification to get a better result than using single method. The result of this research is an implementation of web-based application that developed using PHP language. The document is from horticulture reasearch journal from 2002 until 2009. From 340 documents, 300 document is used for data training and 40 documents is for testing. The accuracy of ACC is 80% and for Naive Bayes classification is 42.5%.
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Judul: Pengaruh vaksin aktif dan inaktif terhadap kekebalan dalam pencegahan penyakit newcastle pada ayam
Abstrak: Penyakit Newcastle adalah penyakit yang bersifat infeksius dan kontagius yang menyerang unggas terutama ayam dan kalkun; menimbulkan kematian, penurunan produksi dan kwalitas telur sehingga menimbulkan kerugian ekonomi yang besar; disebabkan oleh paramyxovirus yang termasuk ke dalam golongan virus yang berinti asam ribonukleat. Virus penyebab penyakit ini terdiri atas beberapa galur yaitu velogenik, mesogenik dan lentogenik. Vaksinasi adalah salah satu cara untuk mencegah timbulnya penyakit dan kerugian yang ditimbulkannya. Vaksin terdiri atas vaksin aktif dan inaktif atau vaksin dalam emulsi minyak. Vaksinasi pada umur dini adalah cara yang paling baik dilakukan. Umur ayam yang tepat mulai dilaksanakan vaksinasi adalah pada umur 4 hari, karena pada saat ini titerantibodi asal induk sudah mulai turun dan kondisi ayam sudah mulai kuat untuk dilakukan vaksinasi jika melakukannya pada ayam umur sehari. ...
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