Analisa Perbandingan Kinerja Algoritma Arithmetic Coding Dan Fibonacci Codes Dalam Kompresi File Audio Menggunakan Metode Perbandingan Eksponensial - Arien Hotma Rotua Nababan (Graha Mitra Edukasi, 2023)
Compression is the process of changing an input data stream into a new data stream that has a smaller data size with the aim of representing digital data with as few bits as possible, but still maintaining the minimum need to reshape the original data. An audio file format is a file format for storing digital audio data on a computer system. Storing this data cannot only be done using the available file formats. Therefore, a file compression process is needed. Arithmetic coding has a compression level that is better or at least the same as Huffman coding, but the compression and decompression times are slow because of the large number of calculation processes that must be carried out. Arithmetic coding is a part of Entropy Encoding which converts data into another form of data by using fewer bits more often and rarely using more character bits. In previous research, this coding technique separated the input message into symbols and exchanged each symbol with a floating point. Fibonacci coding is a universal code that can encode positive integers into binary code in the form of code words. Where the compression process using the Fibonacci code is carried out by reading the file in bytes then changing the byte value into an integer followed by searching for the code word. The Exponential Comparison Method (MPE) is one of the methods of the Decision Support System (DSS) which is used to determine the priority order of alternatives with multiple criteria. MPE is very suitable for ordinal scale assessment. The exponential comparison method has the advantage of reducing bias that may occur in the analysis. The score value that describes the order of priorities becomes large (exponential function) resulting in a more real priority order of decision alternatives.