The study observes the metadata identification and analysis for Document, Audio, Image, and Videos. The process uses MapReduce and Match Aggregate Pipeline to identify, classify, and categories for identification purposes. The inputs are FITS array results and processed in form of XML. The works consist of the extraction process, identification and analysis, classification, and metadata information. The objective is establishing the file information based on volume, variety, veracity, and velocity criteria as part of task identification component in Self-Assignment Data Management. Testing is done for all file types with the number of files and the size of the file according to the grouping. The results show that there is a pattern where the match-aggregate-pipeline has a longer processing time than MapReduce on a small block size, shown in a block size of 64 Mb, 128 Mb, and 256 Mb. But once the block size is magnified the match-aggregate-pipeline has faster processing time at 1024 Mb and 2048 Mb. The results have a contribution in the metadata processing for large files can be done by arranging the block sizes in Match Aggregate Pipeline.

The research has implemented document summarizing system uses TextRank algorithms and Semantic Networks and Corpus Statistics. The use of TextRank allows extraction of the main phrases of a document that used as a sentence in the summary output. The TextRank consists of several processes, namely tokenization sentence, the establishment of a graph, the edge value calculation algorithms using Semantic Networks and Corpus Statistics, vertex value calculation, sorting vertex value, and the creation of a summary. Testing has done by calculating the recall, precision, and F-Score of the summary using methods ROUGE-N to measure the quality of the system output. The quality of the summaries influenced by the style of writing, the selection of words and symbols in the document, as well as the length of the summary output of the system. The largest value of the F-Score is 10% of the length ta of the document with the F-Score 0.1635 and 150 words with the F-Score 0.1623.