Judul: Evaluasi Algoritme Breadth First, Best First, Dan Page Rank Pada Web Crawler
Abstrak: Web crawling is a process by which we gather pages from the web, in order to index them and support a search engine. The objective of crawling is to quickly and efficiently gather as many useful web pages as possible, together with the link structure that interconnects them. The objective of this research is to evaluate Breadth First, Breadth First with Time Constraint, Best First and Page Rank algorithms. The process of collecting web pages consists of the initialization process (keywords and starting URL), inserting a link to the frontier, stoping crawling, take\ing the link from frontier, fetch, parsing and indexing. The focus of web crawler algorithm is determines the next link that will be visited. Based on the precision and opportunity of keywords per algorithm, the result of the evaluation indicates that the page rank algorithm is better than three other algorithms. While based on the complexity of algorithm, the result of the evaluation indicates that the page rank algorithm has higher complexity as compared to three other algorithms. In addition, based on the average fetch time, the result of the evaluation indicates that the best first algorithm is more stable than three other algorithms. Keywords : web crawler, web crawling, breadth first, breadth first with time constraint, best first, page rank, cosine similarity, web crawler evalution, precision values of web crawler, complexity algorithm of web crawler.
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Judul: Sistem Peringkas Teks Otomatis Menggunakan Algoritme Page Rank
Abstrak: With the rapid growth of World Wide Web, a huge amount of information is available and accessible online. People do not have the time to read everything, and yet they have to make critical decisions based on whatever information is available. Automatic text summarization is a technique to assist people in digesting the vast amount of information online. Recently, a number of graph-based approaches, such as PageRank, LexRank, and TextRank, have been suggested for text summarization. Automatic text sllnnnarization is a computerized process of distilling the most important information of a source (or sources) for making a brief version of text(s). This research implements graph-based sunamarization algorithm and similarity using graph-based ranking concept for ranking sentences. The process produces the output in the form of extractive summary that consists of high ranking sentences. The graph-based method applied is PageRank, combined with cosine and content overlap similarity. Evaluation of the summaries uses three human judges and their judgement is compared using kappa measure. The result of our experiment shows that the accuracy of PageRank and cosine similarity is better than PageRank with content overlap similarity. Similarity to title produced the best result than similarity with no title.
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Judul: Dosis minimum vaksin Newcastle disease lassota untuk menggertak pembentukan zat kebal proteksi pada ayam
Abstrak: Penelitian ini bertujuan untuk menentukan dosis minimum vaksin ND Lasota yang diperlukan untuk menggertak pembentukan zat kebal (antibodi) yang dapat melindungi hewan dari infeksi virus ganas dialam. Selain itu diperiksa juga gambaran zat kebal induk bawaan ("maternal antibody") dan titer vaksin yang digunakan. Penelitian dilaksanakan di laboratorium Virologi Fakultas Kedokteran Hewan, Institut Pertanian Bogor selama empat bulan dari bulan Pebruari 1987 sampai bulan Mei 1987. lasil penelitian ini menunjukkan bahwa vaksin dengan dosis 106.3 EID50 dapat menggertak pembentukan zat kebal yang dapat melindungi ayam terhadap infeksi alam secara menyeluruh (100%). Zat kebal induk bawaan masih ditemukan sampai anak ayam berumur 3 minggu walaupun tingkatnya rendah dan tidak bersifat proteksi. Titer vaksin yang digunakan adalah 109.3 EID50 setiap ml.
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