Published: 2023-11-02
Analisis Performa Algoritma Kompresi Data dalam Penyimpanan dan Transfer Data
DOI: 10.35870/ljit.v1i2.2157
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Abstract
In the rapidly developing information era, efficiency in data storage and transfer becomes crucial. This research aims to analyze the performance of various data compression algorithms in the context of data storage and transfer. A literature review was conducted to understand the theoretical basis, types of compression algorithms, and factors influencing performance. The research methodology involves controlled experiments to measure compression ratios, compression and decompression speeds, as well as algorithm adaptability to data variations. The research results provide deep insight into the efficiency of each algorithm in various situations. The conclusion highlights the advantages and disadvantages of specific algorithms, providing practical recommendations for algorithm selection based on application needs.
Keywords
Data Compression Algorithm ; Compression Ratio ; Compression Speed ; Decompression Speed
Article Information
This article has been peer-reviewed and published in the LANCAH: Jurnal Inovasi dan Tren. The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 1 No. 2 (2023)
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Section: Articles
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Published: %750 %e, %2023
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License: CC BY 4.0
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Copyright: © 2023 Authors
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DOI: 10.35870/ljit.v1i2.2157
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Meri Chrismes Aruan
FTIK, Program Studi Teknik Informatika, Universitas Indraprasta PGRI, Jakarta, Indonesia
Wanti Rahayu
FTIK, Program Studi Teknik Informatika, Universitas Indraprasta PGRI, Jakarta, Indonesia
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aws.amazon.com, “Apa itu migrasi data?,” https://aws.amazon.com/id/what-is/data-migration/.
-
Y. Darnita, K. Khairunnisyah, and H. Mubarak, “Kompresi Data Teks Dengan Menggunakan Algoritma Sequitur,” Sistemasi: Jurnal Sistem Informasi, vol. 8, no. 1, pp. 104–113, 2019.
-
A. D. Mahendra, E. Suryani, and A. Aziz, “Analisis Perbandingan Kinerja Kombinasi Algoritma BWT-RLE-MTF-Huffman Dan BWT-MTF-RLE-Huffman Pada Kompresi File,” ITSMART: Jurnal Teknologi dan Informasi, vol. 1, no. 2, pp. 107–115.
-
H. Purwanto, “Penerapan algoritma huffman pada kompresi file wave,” JSI (Jurnal sistem Informasi) Universitas Suryadarma, vol. 2, no. 2, 2018.
-
M. A. Masa and M. Z. Altim, “Perkembangan Dan Analisis Kompresi Data,” LOGITECH, vol. 2, no. 2, pp. 14–20, 2019.
-
A. J. Qasim, R. Din, and F. Q. A. Alyousuf, “Review on techniques and file formats of image compression,” Bulletin of Electrical Engineering and Informatics, vol. 9, no. 2, pp. 602–610, 2020.
-
L. Hiryanto and S. N. Ardhytia, “Algoritma Kompresi Fraktal Sequential dan Paralel untuk Kompresi Citra,” Jurnal Ilmu Komputer dan Informasi, vol. 3, no. 2, pp. 108–117, 2010.
-
A. Nur, H. Yuana, and F. Febrinita, “Aplikasi Kompresi Citra dengan Menggunakan Algoritma Lempel Ziv Welch (LZW),” JATI (Jurnal Mahasiswa Teknik Informatika), vol. 6, no. 2, pp. 684–695, 2022.
-
K. Mahesa, “Rancang Bangun Aplikasi Kompresi Dan Dekompresi Pada Citra Digital Menggunakan Metode Huffman,” Jurnal Processor, vol. 12, no. 1, pp. 948–963, 2017.
-
L. Sodikin, T. F. Putri, and T. Hidayat, “Analisa Kompresi File Teks Menggunakan Algortima Huffman,” Journal ICTEE, vol. 3, no. 1, pp. 10–19, 2022.
-
H. Sulistyanto, “PEMAMPATAN DATA LOSSLESS DENGAN METODE STATIC-ADAPTIVE ARITHMETIC CODING,” 2010.
-
S. Widodo, “Kinerja dan Performa Algoritma Kompressi Lossless Terhadap Objek Citra Digital,” in Industrial Electronic Seminar, 2010.
-
S. Rahma and A. Prapanca, “Analisis Kompresi dan Dekompresi Data Teks dan Audio dengan Algoritma Run Length Encoding (RLE),” Journal of Informatics and Computer Science (JINACS), vol. 2, no. 04, pp. 313–320, 2021.
-
I. K. Jaya and R. Perangin-angin, “Analisa Perbandingan Rasio Kecepatan Kompresi Algoritma Dynamic Markov Compression Dan Huffman,” Sinkron: jurnal dan penelitian teknik informatika, vol. 2, no. 2, pp. 78–85, 2018.
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