Analisis Perbandingan Algoritma Goldbach G0 Dan Algoritma Goldbach G1 Dalam Mengkompresikan File Gambar

 (*)Elfiyana Sinta Sitorus Mail (Universitas Budi Darma, Medan, Indonesia)

(*) Corresponding Author

Abstract

As the world develops, technology for obtaining information quickly becomes more sophisticated and widespread. Various technical means are continuously being developed to enable everyone to successfully share information, especially when sending data such as image files, but large image files cause storage capacity problems and can be difficult to store in image file data. To fix this problem, it is recommended to compress the image file with the appropriate algorithm for best results. To find a suitable compression algorithm, compare the Goldbach Codes G0 and Goldbach Codes G1 algorithms to save image file storage space when sending image files. Compressed image files are also easier and faster to send due to their smaller data size. After testing the system, Goldbach G0 algorithm has compression ratio (Cr) 42%, redundancy (Rd) 57%, and space saving (Ss) 57%, which is better than Goldbach codes G1 algorithm in image file compression process. I understand. During compression and decompression, the Goldbach Codes G0 algorithm takes less time to compress image files than the Goldbach Codes G1 algorithm.

Keywords


Compression; Algorithm Goldbach Codes G0; Goldbach Codes G1

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