Pengamanan Dokumen Digital Menggunakan Kombinasi Algoritma Enkripsi Blowfish dan Encoding Base64

In the digital era, document protection is crucial to safeguard the confidentiality and integrity of organizational information against various security threats. Numerous data breach incidents occur due to weak protection of internal documents that are not properly encrypted. This study aims to develop and evaluate a multi-format digital document security system by combining the Blowfish encryption algorithm with Base64 encoding. Blowfish serves as the main encryption algorithm to convert plaintext into binary ciphertext, while Base64 is used to convert the encrypted output into ASCII text format to facilitate storage and transmission, but not as a primary security mechanism. The system is implemented as a web-based application to enable convenient access and operation through a browser interface. The research methodology includes problem identification, data collection using Excel documents, system design, algorithm implementation, and testing. Functional validation and brute-force resistance tests were conducted. The results show that the system successfully performed encryption and decryption with 100% accuracy on five test files without data loss. The encrypted file size increased by approximately 0.3% due to the encoding process, which remains within acceptable limits. Security testing using CrypTool indicated that the ciphertext could not be deciphered without a valid key, even under systematic key search attempts. The primary contribution of this study is the integration of Blowfish encryption and Base64 encoding into an efficient web-based digital document security system, validated for brute-force resistance, which has not been widely explored in previous research.

Authors

Publication Details

Journal
TEMATIK
Published
2025-07-01
DOI
https://doi.org/10.38204/tematik.v12i1.2316
Primary Topic
Computer Science and Engineering
Type
article
Field-Weighted Citation Impact
0.00
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article

Pengamanan Dokumen Digital Menggunakan Kombinasi Algoritma Enkripsi Blowfish dan Encoding Base64

Muhammad Ziad Ziayuddin, Imelda Imelda
TEMATIK
Computer Science and Engineering
article

Pengamanan Dokumen Digital Menggunakan Kombinasi Algoritma Enkripsi Blowfish dan Encoding Base64

Muhammad Ziad Ziayuddin, Imelda Imelda
article en

Abstract

In the digital era, document protection is crucial to safeguard the confidentiality and integrity of organizational information against various security threats. Numerous data breach incidents occur due to weak protection of internal documents that are not properly encrypted. This study aims to develop and evaluate a multi-format digital document security system by combining the Blowfish encryption algorithm with Base64 encoding. Blowfish serves as the main encryption algorithm to convert plaintext into binary ciphertext, while Base64 is used to convert the encrypted output into ASCII text format to facilitate storage and transmission, but not as a primary security mechanism. The system is implemented as a web-based application to enable convenient access and operation through a browser interface. The research methodology includes problem identification, data collection using Excel documents, system design, algorithm implementation, and testing. Functional validation and brute-force resistance tests were conducted. The results show that the system successfully performed encryption and decryption with 100% accuracy on five test files without data loss. The encrypted file size increased by approximately 0.3% due to the encoding process, which remains within acceptable limits. Security testing using CrypTool indicated that the ciphertext could not be deciphered without a valid key, even under systematic key search attempts. The primary contribution of this study is the integration of Blowfish encryption and Base64 encoding into an efficient web-based digital document security system, validated for brute-force resistance, which has not been widely explored in previous research.

TEMATIKVol. 12(1)
Openalex Percentile: Top 92%
Computer Science and Engineering
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