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: Penggabungan Ciri Citra dan Teks untuk Sistem Pencarian Tumbuhan Obat Indonesia Berbasis Web
Abstrak: This research investigate the effectiveness of image and text fusion for Indonesian medicinal plant search engine based on web application. This research used 51 species of Indonesian medicinal plants and each species consists of 48 images, so the total images used in this research are 2448 images. WeightedSUM is general linear combination formula to combine image and text features. Further research was conducted on the combination of features to get a better result in medicinal plants search engine. Fuzzy Local Binary Pattern (FLBP) is used to extract texture in image processing. This research uses the Probabilistic Neural Network (PNN) to improve image similarity that used in the fusion process. BM25 weighting in document search engine is used to get text similarity. Image and text similarity are combined using WeightedSUM to get the retrieval results. The experimental results show that the fusion of image and text features can improve the performance of retrieval results. In particular, the Average Precision (AVP) has increased from 0.31 to 0.71
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Judul: Granular venereal disease ( GVD ) lepuh kecil pada vagina sapi teori terbentuknya dan cara pengobatannya
Abstrak: Isseponi pada tahun 1887 (dalam Williams, W.L. 1950) pertama sekali menemukan penyakit ini dengan mengamati ada nya lepuh-lepuh atau nodul dan peradangan pada mukosa vulva dan menduga merupakan penyebab terjadinya ketidak suburan dan abortus pada sapi. Sedang beberapa ahli menyatakan bahwa GVD bukan merupakan penyebab terjadinya ketidak suburan dan abortus, hanya kemungkinan adanya infeksi sekunder yang menyebabkan terjadinya sterilitas dan abortus. Sampai sekarang agen penyebab penyakit ini masih belum diketahui dengan pasti, ada yang menyatakan disebabkan oleh virus, bakteri, protozoa ataupun micoplasma. - Masa inkubasi penyakit 2 sampai 3 minggu dan dapat berjalan kronis dan ringan tanpa menimbulkan gangguan dan dapat juga berlangsung akut dan parah. Sering penyakit ini dapat sembuh sendiri tanpa diketahui pemunculannya lebih dahulu sehingga pemilik ternak tidak mengetahui hewannya pernah terserang penyakit Venereal Granular ini. Penularan paling sering terjadi melalui perkawinan alam dimana sapi-sapi jantan dapat berperan sebagai penye bar penyakit ke sapi-sapi betina lain. ...
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