Analisis Teknik Enkripsi Untuk Meningkatkan Keamanan Data Pada Jaringan Komputer
Kata Kunci:
Enkripsi, Keamanan Data, AES, RSA, Jaringan Komputer.Abstrak
Keamanan data pada jaringan komputer merupakan isu krusial di era digital modern, di mana peningkatan volume dan sensitivitas data menuntut sistem perlindungan yang kuat terhadap ancaman siber. Enkripsi menjadi teknik utama untuk menjaga kerahasiaan, integritas, dan autentikasi data yang ditransmisikan melalui jaringan terbuka. Namun, perbedaan karakteristik setiap algoritma enkripsi memengaruhi efisiensi, performa, dan tingkat keamanan sistem secara keseluruhan. Penelitian ini bertujuan untuk menganalisis dan membandingkan performa beberapa teknik enkripsi, yaitu AES, RSA, dan Blowfish, dalam meningkatkan keamanan data pada jaringan komputer, serta menentukan algoritma yang paling optimal dari aspek kecepatan, efisiensi, dan ketahanan terhadap serangan. Penelitian ini menggunakan pendekatan eksperimen kuantitatif dengan pengujian langsung terhadap ketiga algoritma menggunakan dataset berukuran 1 MB, 10 MB, dan 100 MB. Pengujian dilakukan menggunakan bahasa pemrograman Python dengan parameter pengukuran waktu enkripsi-dekripsi, throughput, serta penggunaan CPU dan memori. Hasil menunjukkan bahwa AES memiliki performa terbaik dengan waktu enkripsi tercepat (0,21–17,6 detik) dan throughput tertinggi (hingga 5,68 MB/s), serta efisiensi sumber daya tertinggi. Blowfish menunjukkan hasil moderat, sedangkan RSA memerlukan waktu dan sumber daya jauh lebih besar. Penelitian ini menyimpulkan bahwa AES merupakan algoritma paling efektif dan efisien untuk sistem jaringan modern, sementara RSA lebih cocok untuk pertukaran kunci dan autentikasi. Studi lanjutan disarankan untuk mengembangkan enkripsi berbasis post-quantum cryptography guna menghadapi ancaman komputasi kuantum di masa depan.
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REFERENSI
[1] F. P. E. Putra, D. E. Arissandi, A. Rofiqi, and M. F. Hidayat, “Pemanfaatan Mikrotik Dalam Manajemen Bandwidth Pada Jaringan Sekolah,” 2025, researchgate.net. [Online]. Available: https://www.researchgate.net/profile/Fauzan-Eka-Putra-2/publication/392420575_Pemanfaatan_Mikrotik_Dalam_Manajemen_Bandwidth_Pada_Jaringan_Sekolah/links/6848fab46b5a287c304a61ca/Pemanfaatan-Mikrotik-Dalam-Manajemen-Bandwidth-Pada-Jaringan-Sekolah.pdf
[2] F. P. E. Putra, D. A. M. Putra, A. Firdaus, and ..., “Analisis kecepatan dan kinerja jaringan 5G (generasi ke 5) pada wilayah perkotaan,” … J. Informatics, 2023.
[3] F. P. E. Putra, S. R. Sutarsih, S. Sofiyulloh, and ..., “Optimalisasi Perancangan Aplikasi Manajemen Data Koloman, Di Desa Pulau Mandangin Sampang–Madura Berbasis Website,” 2024, jurnal.univrab.ac.id. [Online]. Available: https://jurnal.univrab.ac.id/index.php/rabit/article/download/4840/1965
[4] F. P. E. Putra, M. Ghummah, M. Amrullah, and R. Hidayatullah, “Studi Kinerja Mesh Network untuk Penerapan Internet of Things (IoT) di Lingkungan Perkotaan,” 2025, researchgate.net.
[5] F. P. E. Putra, K. Mufidah, R. M. Ilhamsyah, and ..., “Tinjauan performa RouterOS Mikrotik dalam jaringan internet: Analisis kinerja dan kelayakan,” Digit. …, 2023.
[6] F. P. E. Putra, A. M. U. Solichin, and ..., “Pemanfaatan Teknologi Wireless dan Mobile Network Berbasis 5G Untuk Pemerataan Akses Jaringan di Indonesia,” Infotek J. …, 2025, [Online]. Available: https://e-journal.hamzanwadi.ac.id/index.php/infotek/article/view/30559
[7] F. P. E. Putra, L. Fitriyah, Z. Naimah, and ..., “Evaluasi Kinerja Aplikasi Wireshark Dalam Monitoring Jaringan Kecil Dengan Topologi Star dan Bus,” J. Ilm. Ilk. …, 2025.
[8] F. P. Eka Putra, M. N. Arifin, K. Zulfana Imam, E. Saputra, and Sofiyullah, “Pengembangan Sistem Informasi Laboratorium Terintegerasi Sistem Akademik Menggunakan Agile Scrum,” J. Inf. dan Teknol., pp. 109–119, 2023, doi: 10.37034/jidt.v5i2.367.
[9] N. Haidar Hari, F. P. Eka Putra, U. Hasanah, S. R. Sutarsih, and Riyan, “Transformasi Jaringan Telekomunikasi dengan Teknologi 5G: Tantangan, Potensi, dan Implikasi,” J. Inf. dan Teknol., pp. 146–150, 2023, doi: 10.37034/jidt.v5i2.357.
[10] F. P. E. Putra, N. D. Saputri, F. Rosi, and R. Loati, “Optimalisasi Infrastruktur Cloud Networking melalui Inte-grasi SDN, NFV, dan Multi-Cloud,” 2025, researchgate.net. [Online]. Available: https://www.researchgate.net/profile/Fauzan-Eka-Putra-2/publication/392411211_Optimalisasi_Infrastruktur_Cloud_Networking_melalui_Integrasi_SDN_NFV_dan_Multi-Cloud/links/6848f8b9df0e3f544f5e49f2/Optimalisasi-Infrastruktur-Cloud-Networking-melalui-Integras
[11] J. Xu et al., “A durable, breathable, and weather-adaptive coating driven by particle self-assembly for radiative cooling and energy harvesting,” Nano Energy, vol. 124, 2024, doi: 10.1016/j.nanoen.2024.109489.
[12] M. Boudouane, L. Elmahni, R. Zriouile, and S. A. Ait El Ouahab, “Advancing solar energy harvesting: Artificial intelligence approaches to maximum power point tracking,” Int. J. Power Electron. Drive Syst., vol. 16, no. 1, pp. 55–69, 2025, doi: 10.11591/ijpeds.v16.i1.pp55-69.
[13] Y. Chen, X. Wang, Z. Liu, J. Cui, M. Osmani, and P. Demian, “Exploring Building Information Modeling (BIM) and Internet of Things (IoT) Integration for Sustainable Building,” Buildings, vol. 13, no. 2, 2023, doi: 10.3390/buildings13020288.
[14] D. Sharma et al., “Securing X-Ray Images in No Interest Region (NIR) of the Normalized Cover Image by Edge Steganography,” IEEE Access, vol. 12, pp. 168672–168689, 2024, doi: 10.1109/ACCESS.2024.3467167.
[15] L. Ding, A. Datta, and S. Sen, “Biophysical Modeling of Capacitive Electro-Quasistatic Human Body Powering,” IEEE Trans. Biomed. Eng., vol. 72, no. 9, pp. 2593–2608, 2025, doi: 10.1109/TBME.2025.3547738.
[16] F. J. Cañamero, F. C. Buroni, and L. Rodríguez-Tembleque, “Influence of the porosity and auxeticity of matrices and interfacial integrity on the performance of KNN-based piezocomposites,” Eur. J. Mech. A/Solids, vol. 114, 2025, doi: 10.1016/j.euromechsol.2025.105754.
[17] H. Li et al., “EIUAPA: an efficient and imperceptible universal adversarial attack on audio classification models,” Int. J. Comput. Sci. Eng., vol. 28, no. 4, pp. 434–445, 2025, doi: 10.1504/IJCSE.2025.147609.
[18] M. Zhang, S. Chen, J. Shen, and W. Susilo, “PrivacyEAFL: Privacy-Enhanced Aggregation for Federated Learning in Mobile Crowdsensing,” IEEE Trans. Inf. Forensics Secur., vol. 18, pp. 5804–5816, 2023, doi: 10.1109/TIFS.2023.3315526.
[19] X. Qiu et al., “Joint Device Charging and Fresh Data Retrieval with Mobile Edge Device in Wireless-Powered IoT Systems,” IEEE Trans. Consum. Electron., vol. 70, no. 4, pp. 7385–7397, 2024, doi: 10.1109/TCE.2024.3419128.
[20] W. Wang, W. Ni, H. Tian, Y. C. Eldar, and R. Zhang, “Multi-Functional Reconfigurable Intelligent Surface: System Modeling and Performance Optimization,” IEEE Trans. Wirel. Commun., vol. 23, no. 4, pp. 3025–3041, 2024, doi: 10.1109/TWC.2023.3305005.
[21] W. Sheng, H. Xiang, L. Gao, J. Wang, J. Liang, and Z. Zhang, “Whole-process analysis and implementation of a self-powered wireless health monitoring system for railway bridges: Theory, simulation and experiment,” Eng. Struct., vol. 316, 2024, doi: 10.1016/j.engstruct.2024.118584.
[22] Z. Bai, J. Shi, Z. Li, M. Li, and X. Liao, “An MA-HPPO Approach for Multi-UAV Data Collection,” IEEE Trans. Wirel. Commun., vol. 23, no. 12, pp. 17974–17986, 2024, doi: 10.1109/TWC.2024.3458194.
[23] M. Awais, W. Khan, T. Akram, and Y. Nam, “Energy-Efficient Discrete Cosine Transform Architecture Using Reversible Logic for IoT-Enabled Consumer Electronics,” IEEE Access, vol. 13, pp. 12292–12307, 2025, doi: 10.1109/ACCESS.2025.3528261.
[24] J. Zhao, J. Yang, J. Chen, C. Hou, Y. Wang, and Y. Wang, “A stretchable triboelectric nanogenerator with an organohydrogel as electrode for biomechanical energy harvesting and self-powered sensing,” Mater. Today Commun., vol. 49, 2025, doi: 10.1016/j.mtcomm.2025.113704.
[25] J. Kuriakose, S. Joshi, and A. K. Bairwa, “EMBN-MANET: A method to Eliminating Malicious Beacon Nodes in Ultra-Wideband (UWB) based Mobile Ad-Hoc Network,” Ad Hoc Networks, vol. 140, 2023, doi: 10.1016/j.adhoc.2022.103063.
[26] A. A. Khan, R. Ghodhbani, A. Alsufyani, N. Alsufyani, and M. A. Mohamed, “Leveraging blockchain-integrated explainable artificial intelligence (XAI) for ethical and personalized healthcare decision-making: a framework for secure data sharing and enhanced patient trust,” J. Supercomput., vol. 81, no. 15, 2025, doi: 10.1007/s11227-025-07844-0.
[27] Y. Meng, Z.-Q. Lu, H. Ding, and L.-Q. Chen, “Plate theory based modeling and analysis of nonlinear piezoelectric composite circular plate energy harvesters,” Nonlinear Dyn., vol. 112, no. 7, pp. 5129–5149, 2024, doi: 10.1007/s11071-024-09308-1.
[28] A. Hussain, T. Hussain, R. W. Attar, A. Alhomoud, M. M. Alnfiai, and R. Alsagri, “Energy-efficient synchronization for body sensor network in the metaverse: an optimized connectivity approach,” Eurasip J. Wirel. Commun. Netw., vol. 2025, no. 1, 2025, doi: 10.1186/s13638-025-02433-4.
[29] C. Lin, Y. Liu, and D. Shang, “ORSAS: An Output Row-Stationary Accelerator for Sparse Neural Networks,” IEEE Access, vol. 11, pp. 44123–44135, 2023, doi: 10.1109/ACCESS.2023.3272564.
[30] P. Guo, S. Xu, and W. Liang, “A cloud-assisted anonymous and privacy-preserving authentication scheme for internet of medical things,” Comput. Secur., vol. 157, 2025, doi: 10.1016/j.cose.2025.104614.
[31] P. Jagdish Kumar and N. Neduncheliyan, “BSA-SGRU-A Novel Deep Learning Framework for Alleviate the Multiple Attacks in IoT-Cloud Environment,” J. Comput. Cogn. Eng., vol. 4, no. 3, pp. 309–318, 2025, doi: 10.47852/bonviewJCCE42023061.
[32] D. Qiao, M. Li, S. Guo, J. Zhao, and B. Xiao, “Resources-Efficient Adaptive Federated Learning for Digital Twin-Enabled IIoT,” IEEE Trans. Netw. Sci. Eng., vol. 11, no. 4, pp. 3639–3652, 2024, doi: 10.1109/TNSE.2024.3382206.
[33] V. Goutham and V. P. Harigovindan, “NOMA Based Cooperative Relaying Strategy for Underwater Acoustic Sensor Networks under Imperfect SIC and Imperfect CSI: A Comprehensive Analysis,” IEEE Access, vol. 9, pp. 32857–32872, 2021, doi: 10.1109/ACCESS.2021.3060784.
[34] N.-S. Pham, S. Shin, L. Xu, W. Shi, and T. Suh, “Cross-Filter Structured Pruning for Efficient Sparse CNN Acceleration,” IEEE Access, vol. 13, pp. 129461–129475, 2025, doi: 10.1109/ACCESS.2025.3587027.
[35] D. Shi, K.-M. Lei, R. P. Martins, and P.-I. Pui-In, “A 0.35-0.5-V 0.0136-mm2 12 -MHz Digital Frequency-Locked Loop With 1.06%/V Line Sensitivity in 65-nm CMOS,” IEEE Trans. Circuits Syst. II Express Briefs, vol. 72, no. 3, pp. 459–463, 2025, doi: 10.1109/TCSII.2025.3531710.
[36] F. Ge, C. Han, and W. Wang, “Recursive Filtering for Two-Dimensional Markov Jump Linear System With Time Correlated Multiplicative Noises and Energy Harvesting Constrains,” Optim. Control Appl. Methods, vol. 46, no. 4, pp. 1633–1649, 2025, doi: 10.1002/oca.3283.
[37] S. Gnanavel, S. Muruganandam, G. Balamurugan, and N. Duraimurugan, “A Real Time Node Identity Based Multi Algorithm Framework for Enhancing MANET Performance,” Int. J. Intell. Syst. Appl. Eng., vol. 11, no. 4, pp. 546–555, 2023, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174843087&partnerID=40&md5=1841b9e1d507b06df6c7f5a095ccdb7d
[38] W. Dang, X. Wu, J. Qu, and Z. Chen, “An inerter-enhanced nonlinear piezoelectric–electromagnetic hybrid energy harvester,” Arch. Appl. Mech., vol. 95, no. 4, 2025, doi: 10.1007/s00419-025-02797-5.
[39] O. A. Alfahad, H. Saied, E. Malaekah, A. A. Rashdi, M. Emam, and M. Bakouri, “An Auto-Adjusting Algorithm to Enhance Indoor Localization Accuracy: A Real-Time Experimental Analysis,” IEEE Access, vol. 13, pp. 29739–29753, 2025, doi: 10.1109/ACCESS.2025.3541796.
[40] Y. Ma, R. Wu, Y. Zhang, Y. Shang, and L. Zhu, “Throughout Maximization for IRS-Assisted WPCN With Hybrid TDMA-NOMA Scheme,” IEEE Access, vol. 13, pp. 23384–23398, 2025, doi: 10.1109/ACCESS.2025.3537988.
[41] M. Aljebreen, M. Obayya, H. Mahgoub, S. S. Alotaibi, A. Mohamed, and M. A. Hamza, “Chaotic Equilibrium Optimizer-Based Green Communication With Deep Learning Enabled Load Prediction in Internet of Things Environment,” IEEE Access, vol. 12, pp. 258–267, 2024, doi: 10.1109/ACCESS.2023.3345803.
[42] B. Zheng, K. Zhuo, H. Zhang, and H.-X. Wu, “A novel airborne greedy geographic routing protocol for flying Ad hoc networks,” Wirel. Networks, vol. 30, no. 5, pp. 4413–4427, 2024, doi: 10.1007/s11276-022-03030-9.
[43] R. Sun, H. Ma, S. Zhou, Z. Li, and L. Cheng, “A direction-adaptive ultra-low frequency energy harvester with an aligning turntable,” Energy, vol. 311, 2024, doi: 10.1016/j.energy.2024.133273.
[44] V. Singh, S. Rana, R. Bokolia, A. K. Panwar, R. Ramcharan, and B. Singh, “Electrospun PVDF-MoSe2 nanofibers based hybrid triboelectric nanogenerator for self-powered water splitting system,” J. Alloys Compd., vol. 978, 2024, doi: 10.1016/j.jallcom.2024.173416.
[45] M. Pandian, D. Devaraj, H. K. Sahu, A. S. Sindhu, A. Angappan, and N. V Watson, “Optimizing Large-Scale RFID Networks With Energy-Efficient Dynamic Cluster Head Selection: A Performance Improvement Approach,” IEEE Access, vol. 12, pp. 41042–41055, 2024, doi: 10.1109/ACCESS.2024.3378528.
[46] S. Jiang, J. Li, X. Zhang, H. Yue, H. Wu, and Y. Zhou, “Secure and Privacy-Preserving Energy Trading With Demand Response Assistance Based on Blockchain,” IEEE Trans. Netw. Sci. Eng., vol. 11, no. 1, pp. 1238–1250, 2024, doi: 10.1109/TNSE.2023.3321754.
[47] X. Nie, D. Li, H. Cui, and M. Chen, “Harvesting Vibration Energy of a Longitudinally Vibrating Rod within a Width Frequency Band by Designing Variable Stiffness Equipment,” Int. J. Struct. Stab. Dyn., vol. 25, no. 12, 2025, doi: 10.1142/S0219455425501238.
[48] W. Wang, W. An, and B. Song, “Effect of wing morphing on stability and energy harvesting in albatross dynamic soaring,” Chinese J. Aeronaut., vol. 37, no. 11, pp. 317–334, 2024, doi: 10.1016/j.cja.2024.06.013.
[49] A. K. Singh and R. Jaiswal, “Analysis on transverse vibration of piezo-electro-magneto-thermoelastic composite nanobeams under distinct Green–Naghdi III phase lag models,” Eur. J. Mech. A/Solids, vol. 113, 2025, doi: 10.1016/j.euromechsol.2025.105702.
[50] R. J. Lontaan, O. Lengkong, and J. Waworundeng, “Comparison Analysis of Fingerprinting and Dead Reckoning Methods in Indoor Positioning System.” [Online]. Available: https://core.ac.uk/download/pdf/567992741.pdf
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