Article Per Year (5 Year)
p-Index From 2019 - 2024
0.408
P-Index
This Author published in this journals
All Journal TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer
Mahardiko, Rahutomo
Unknown Affiliation
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
RAW DATA SECURITY BY USING ELGAMAL AND SHA 256 PUBLIC KEY ALGORITHM Surya Permana, Indra; Hidayat, Taufik; Mahardiko, Rahutomo
TEKNOKOM Vol. 4 No. 1 (2021): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (163.842 KB) | DOI: 10.31943/teknokom.v4i1.53

Abstract

The development of information technology has grown exponentially and various of data collections and its method has been obtained. In the era of big data, data has now become an asset that held important values, while in the implementation of data delivery, it clearly is not always safe. One of the method to secure data delivery is data encryption using Cryptography. Cryptography provides an encryption service to secure data delivery by transforming it to random values so that it can no longer be read. The goal in this study was to produce an application that could be used to encrypt data, using ElGamal's cryptography method and hash checking using the SHA256 algorithm. After encryption, to ensure the encrypted data is still the original data without any changes or manipulation by unauthorized 3rd party then done by checking the hash generated using SHA256 algorithm. The data used in this study was a sample of raw data from the ATPWTP survey (ability to pay and willing to pay) conducted by the BPS Cirebon (Central Statistics) in 2019 and the data was in the form of Excel and txt files. The encryption process resulted in a cipher larger than the plaintext and takes longer for the data encryption process than during the data cipher decryption process.
MOBILE SCANNER ADOPTION ANALYSIS BETWEEN EMPLOYMENT AND EDUCATIONAL BACKGROUND – AN ANALYSIS OF LOGISTIC REGRESSION Permana, Indra Surya; Hidayat, Taufik; Mahardiko, Rahutomo
TEKNOKOM Vol. 4 No. 2 (2021): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (280.25 KB) | DOI: 10.31943/teknokom.v4i2.56

Abstract

As of today, the mobile apps may be downloaded everywhere. The development of mobile apps depends on the type of the work. An increasing use of mobile app is scanner apps due to an easy use. This paper presents the regression analysis on employment and educational background of the mobile scanner app because this research used category in the questionnaire. The use of logistic regression is to prove that any different comparisons are detected between employment and educational background so that the use of mobile scanner can be optimally used. The results show that educational background and employment have vital roles for mobile scanner adoption. This study also proves that previous researches on mobile scanner adoption were true for UTAUT model and comparison analysis.
Co-Authors Indra Surya Permana Taufik Hidayat