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All Journal Sharia Oikonomia Law Journal Journal of Computer Science Advancements Journal of Moeslim Research Technik Journal of Tecnologia Quantica Journal of Loomingulisus ja Innovatsioon Research of Scientia Naturalis
Aslam, Bilal
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Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Physics Other

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Journal : Journal of Computer Science Advancements

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Big Data Analysis to Predict Consumption Patterns in Smart Cities Susilo, Anto; Prasetiyo, Rachmat; Aslam, Bilal; Farah, Rina
Journal of Computer Science Advancements Vol. 3 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v3i1.1535

Abstract

The rapid development of smart cities has increased the demand for efficient resource management and personalized services, where understanding consumption patterns is crucial. Big data analysis offers a powerful tool for predicting these patterns, enabling city planners and service providers to make data-driven decisions to enhance urban living quality. This study aims to utilize big data analytics to predict consumption patterns across various sectors in smart cities, including energy, water, and transportation. By leveraging large datasets, this research seeks to provide actionable insights for optimizing resource allocation and anticipating future consumption demands. The methodology involves collecting and analyzing data from multiple sources, such as IoT sensors, public utility records, and social media, to identify consumption trends. Machine learning algorithms, including time series analysis and clustering, were applied to detect patterns and forecast demand. Results indicate that big data analytics can accurately predict consumption fluctuations, with an 85% accuracy in energy demand forecasting and a 78% accuracy in water usage prediction. The findings highlight correlations between demographic factors and consumption, providing a comprehensive understanding of urban needs. The study concludes that big data analysis is a valuable approach to managing resources effectively in smart cities. By predicting consumption patterns, city planners can proactively address demand surges, reduce waste, and improve resource distribution, ultimately supporting sustainable urban growth. Implementing these insights could significantly enhance smart city efficiency and resilience.
ENCRYPTION APOCALYPSE? PREPARING DATA SECURITY FOR THE QUANTUM COMPUTING ERA Iqbal, Kiran; Ali, Zainab; Aslam, Bilal
Journal of Computer Science Advancements Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v3i4.3338

Abstract

The imminent maturation of quantum computing threatens to nullify the mathematical hardness underpinning global Public Key Infrastructure, creating an urgent “Harvest Now, Decrypt Later” vulnerability. This study investigates the operational feasibility of transitioning to NIST-standardized Post-Quantum Cryptography (PQC) protocols within heterogeneous network environments. Utilizing a rigorous quantitative benchmarking framework, we evaluated the performance of lattice-based primitives, specifically ML-KEM and ML-DSA, against classical standards across high-performance servers and resource-constrained IoT devices. Empirical data reveals a fundamental architectural paradigm shift: while PQC algorithms exhibit superior computational execution speeds, they introduce severe transmission overheads, resulting in memory saturation and packet fragmentation on edge hardware. Results demonstrate that hybrid encryption schemes provide valid risk mitigation but incur statistically significant latency penalties due to expanded artifact sizes. We definitively conclude that the “Encryption Apocalypse” is primarily a bandwidth and memory bottleneck rather than a computational one, mandating the immediate deployment of adaptive crypto-agility frameworks to manage the infrastructural constraints of the post-quantum era.
Co-Authors A, Muhammad Firdaus Ali, Zainab Anggita, Marloni Arnes Yuli Vandika Farah, Rina Herri Trisna Frianto, Herri Trisna Hussain, Sara Iqbal, Kiran Omar Ahmad Prasetiyo, Rachmat Shah, Ahmed Sharipov, Rustambek Susilo, Anto Tariq, Usman