Kompresi Data Teks Menggunakan Autoencoder Neural Network (AENN)

Authors

Keywords:

kompresi, dekompresi, AENN

Abstract

salah satu jenis data adalah data teks. Data teks biasanya dikodekan dalam bentuk kode ASCII yang memiliki panjang binner 8. Kompresi data teks bertujuan untuk mengurangi pemakaian ruang penyimpanan pada memori. Penelitian ini menggunakan Auto-Encoder Neural Network (AENN). Hasil dari penelitian ini menghasilkan rasio sebesar 88,62%, namun masih ada keterbasan jika panjang asli ganjil maka setelah didekompresi menghasilkan panjang yang genap dan keterbasan pembagi hidden yang menyebabkan data tidak kembali ke aslinya.

References

Dipalee Gupta, S.C., Discrete Wavelet Transform for Image Processing. International Journal of Emerging Technology and Advanced Engineering (IJETAE), 2015. 4(3): p. 598-602.

M A Budiman, D.R., On Using Goldbach G0 Codes and Even-Rodeh Codes for Text Compression on Using Goldbach G0 Codes and Even-Rodeh Codes for Text Compression. IOP Conf. Series: Materials Science and Engineering, 2017. 180: p. 1-5.

LeCun, Y., Y. Bengio, and G. Hinton, Deep learning. Nature, 2015. 521(7553): p. 436-44.

Jingfei Jiang, R.H., Dongsheng Wang, Jinwei Xu, Yong Dou Performance of the fixed-point autoencoder. Tehnicki vjesnik - Technical Gazette, 2016. 23(1): p. 77-82.

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Published

2018-04-02

Issue

Vol. 3 No. 1 (2018): Prosiding Seminar Nasional Ilmu Komputer dan Teknologi Informasi (SAKTI)

Section

Articles

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