Dwi Julianingsih
Alfabet Inkubator Indonesia

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Leveraging Blockchain Technology to Strengthen Cybersecurity in Financial Transactions: A Comprehensive Analysis David Arian Yusuf; Rio Wahyudin Anugrah; Maulana Arif Komara; Dwi Julianingsih; Emily Garcia
CORISINTA Vol 1 No 2 (2024): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v1i2.33

Abstract

In the rapidly evolving digital landscape, financial transactions are increasingly vulnerable to cyber threats, necessitating advanced security measures beyond traditional methods like encryption and firewalls. This study explores the potential of blockchain technology as a robust framework for enhancing cybersecurity protocols in financial transactions. The primary objective is to assess how blockchain’s decentralized, transparent, and cryptographic features can mitigate risks such as fraud, unauthorized access, and data breaches. Employing a quantitative experimental design, the study simulated financial transactions on a blockchain platform and analyzed historical data on security breaches. The results indicate that blockchain technology significantly improves data security, with a 98\% effectiveness rate in preventing and detecting breaches. However, challenges such as scalability, regulatory compliance, and high energy consumption were also identified. The findings suggest that while blockchain holds considerable promise for securing financial transactions, further innovation is necessary to address its limitations and fully leverage its capabilities in the financial sector.
Leveraging Big Data Analytics for Strategic Marketing Optimization: Insights and Impacts Muhammad Faizal Fazri; Tarisya Ramadhan; Dwi Apriliasari; Dwi Julianingsih; Arabella Fitzroy
CORISINTA Vol 1 No 2 (2024): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v1i2.39

Abstract

In the digital era, Big Data Analytics has emerged as a crucial tool for optimizing marketing strategies. This research explores the integration of Big Data into marketing, aiming to identify effective analytical techniques and their impact on marketing outcomes. The study utilized secondary data from various sources, including sales transactions, social media interactions, customer demographics, and web analytics. The analysis process involved data cleaning, integration, predictive modeling, clustering, sentiment analysis, and data visualization. The findings reveal that promotional campaigns and seasonal discounts significantly boost sales, with customer segmentation identifying three key groups: discount hunters, loyal customers, and occasional shoppers. Sentiment analysis shows positive customer feedback, though logistics-related issues warrant improvement. These results underscore the importance of targeted and personalized marketing strategies driven by data insights. The research contributes to marketing theories by providing empirical evidence on the effectiveness of Big Data Analytics in enhancing marketing strategies. Further research is recommended to explore its applicability across different industries, incorporate more diverse data sources, and utilize advanced analytical techniques to refine marketing strategies.