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All Journal Journal of Computer Science and Research International Journal of Enterprise Modelling
Alesha, Aisyah
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Transportation

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Journal : Journal of Computer Science and Research

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Quantum distributed data processing for enhanced big data analysis Alesha, Aisyah; Jr , Cappel Bibri; Dhote , Horvath
Journal of Computer Science and Research (JoCoSiR) Vol. 1 No. 4 (2023): Oct: Computing Quantum and Related Fields
Publisher : Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) Provinsi Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65126/jocosir.v1i4.28

Abstract

This research explores the paradigm of Quantum Distributed Data Processing (QDDP) and its transformative potential in the realm of big data applications. Focusing on a Quantum Search Algorithm applied to a distributed dataset, the study illuminates key principles of quantum computing, including superposition and parallelism. Through a numerical example, the efficiency gains and scalability of the algorithm are demonstrated, showcasing its ability to revolutionize distributed data processing. The research underscores the importance of addressing challenges such as quantum error correction and hardware limitations for practical implementation. The findings highlight the considerable advantages of QDDP in handling large-scale distributed data and open avenues for future research, including the optimization of quantum algorithms for diverse applications and the exploration of hybrid quantum-classical approaches. This research contributes to the evolving landscape of quantum computing, providing valuable insights into the potential of Quantum Distributed Data Processing to redefine the efficiency and scope of big data analysis in various domains.
Enhancing Electoral Decision-Making: A Social Learning Network Election Decision Support System Utilizing AHP and PROMETHEE Methods Alesha, Aisyah; Simbolon , Romasinta; Batubara, Juliana; Panjaitan, Firta Sari
Journal of Computer Science and Research (JoCoSiR) Vol. 2 No. 1 (2024): Jan: CNN and Artificial
Publisher : Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) Provinsi Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65126/jocosir.v2i1.36

Abstract

This In today's digital age, the intersection of technology, democracy, and citizen participation has become increasingly prominent. This research explores the development and application of a Social Learning Network Election Decision Support System (SLNEDSS) using Analytic Hierarchy Process (AHP) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) methods to enhance electoral decision-making processes. By leveraging social learning networks as platforms for information dissemination and deliberative discourse, SLNEDSS empowers citizens to make informed choices that reflect their values, aspirations, and preferences. The integration of AHP and PROMETHEE methods within SLNEDSS provides users with structured frameworks for evaluating electoral alternatives, synthesizing stakeholder preferences, and facilitating transparent and systematic decision-making processes. Through empirical studies, the effectiveness of SLNEDSS in enhancing the quality and inclusivity of electoral outcomes is demonstrated, highlighting its transformative potential in shaping the future of democratic governance. The research also identifies challenges and limitations associated with SLNEDSS, such as algorithmic biases and user adoption, and suggests directions for future research to address these shortcomings. Ultimately, this research contributes to advancing the frontiers of knowledge and innovation in the field of electoral decision support systems, paving the way for a more informed, inclusive, and responsive democracy in the digital age.
Co-Authors Abubakullo, Abubakullo Dhote , Horvath Jr , Cappel Bibri Juliana Batubara Lee , Ricardo Panjaitan, Firta Sari Simbolon , Romasinta