<![CDATA[Data transmission and data storage cost money. The more information being dealt with, thehigher the cost is needed. In spite of this, most digital data are not stored in the mostcompact form. Rather, they are stored in whatever way makes them easiest to use, such as:ASCII text from word processors, binary code that can be executed by a computer, etc.Typically, these easy-to-use encoding methods require larger size data files than theyactually need to represent the information. Data compression is the general term for thevarious algorithms and programs developed to address this problem. The aim of datacompression is to reduce redundancy in stored data or transmitted data, thus increasingeffective data density. A compression program is used to convert data from an easy-to-useformat to one optimized for compactness. In this paper, we examine and analyze two basicmethods in data compression called Run Length Encoding and Arithmetic coding. Aframework for evaluation and comparison of these two methods is constructed and appliedto the algorithms presented. Comparisons of both theoretical and empirical natures arebriefly reported in this paper. The compression programs for these two methods of datacompression are developed using Java programming language. The program is used tocompress number of different sizes document type files to measure the time spent for thecompression, the time to reconstruct and the size of the compressed data files to get thecompression ratio. The result indicated that arithmetic coding method has compression ratio1,14 up to 2,61 higher than run length encoding while it takes times 1,114 â1,564 and 2,85 â5,635 longer than time needed by Run Length encoding methods. We can conclude that thereare typical tradeoffs between the amount of compression, the runtime, and the quality of thereconstruction. Depending on the application, one might be more important than anotherand one would want to pick the method appropriately.Keywords: Kompresi Data, Run Length Encoding, Arithmetic Coding, Compression ratio.]]>
