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All Journal INTEGER: Journal of Information Technology Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK)
Muchamad Kurniawan
ITATS
Computer Science & IT Electrical & Electronics Engineering

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Journal : INTEGER: Journal of Information Technology

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Algoritma Steganografi untuk Pengamanan Data Teks ke dalam Citra Digital Menggunakan XOR Sederhana Muchamad Kurniawan; Siti Agustini
INTEGER: Journal of Information Technology Vol 3, No 2 (2018)
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2018.v3i2.416

Abstract

Kerahasiaan data atau informasi merupakan hal yang sangat penting untuk dijaga dari seseorang yang tidak berhak atas data tersebut. Salah satu solusi untuk pengamann data adalah dengan steganografi. Steganografi merupakan ilmu untuk penyisipan informasi rahasia ke dalam pesan yang lain. Pada penelitian ini, konsep steganografi menggunakan pesan teks yang disembunyikan ke dalam suatu citra digital. Citra yang digunakan adalah citra dalam bentuk grayscale. Penelitian dilakukan sebanyak 5 kali dengan ukuran pesan teks yang berbeda-beda. Hasilnya, system steganografi berjalan dengan baik dimana semua pesan teks dapat dienkripsi dan didekripsi kembali. Running time akan semakin tinggi ketika ukuran pesan teks semakin besar dan begitu juga dengan nilai entropy sehingga tingkat keamanan dari proses steganografi ini semakin tinggi. Kata Kunci: Steganografi, XOR, running time, entropy.
Implementasi Multilayer Perceptron Pada Jaringan Saraf Tiruan Untuk Memprediksi Nilai Valuta Asing Tommy Ferdian Hadimarta; Rani Rotul Muhima; muchamad kurniawan
INTEGER: Journal of Information Technology Vol 5, No 1: April 2020
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2020.v5i1.909

Abstract

Abstract. In the context of FOREX investment, the fluctuation of currency becomes a common thing in which movement is greatly influenced by supply and demand. If the demand is higher, the price will increase and conversely, if the supply is higher, the price will go downward. There is a principle that the behavior of price patterns will repeat randomly and make unpredictable movement of FOREX. These patterns of currency fluctuation have deceived many investors and brought losses and even capital failure. Basically, the value of foreign exchange belongs to the data of time series and Multilayer Perceptron is very suitable to process data of time series as it is often used to make prediction. Therefore, this research aimed at implementing Multilayer Perceptron in the artificial nerve network for predicting the value of foreign exchange on the available resources using the attributes of open, high, low, and close. To process the data from the existing attributes, there must be initialization first in X1 (open), X2 (high), and X3 (low) as the inputs and Y (close) as the data target, and then they were normalized so as to calculate sigmoid. The increasing number of epoch does not guarantee that the errors will be smaller. On the contrary, perhaps, the error value will increase. The best result of training occurred by epoch 200 and learning rate 3 within the smallest values of MSE 281.02518, MAD 13.168, and deviation standard 10.294.
Co-Authors Danang Haryo Sulaksono Firdaus Alam Hudi Rani Rotul Muhima Siti Agustini Tommy Ferdian Hadimarta