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The Influence of Personalized Marketing on Customer Engagement and Customer Lifetime Value Sayuti, Atkhmad Fauzi; Iqbal, Kiran; Ali, Zainab
Journal Markcount Finance Vol. 3 No. 2 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jmf.v3i1.2064

Abstract

Personalized marketing has emerged as a critical strategy for enhancing customer engagement and customer lifetime value (CLV) in today’s competitive business environment. By leveraging customer data and advanced analytics, businesses can deliver tailored experiences that resonate with individual preferences and behaviors. This study examines the influence of personalized marketing on customer engagement and CLV, focusing on its impact on customer satisfaction, loyalty, and long-term profitability. The research aims to identify effective strategies for implementing personalized marketing and propose recommendations for maximizing its impact on customer relationships. Using a mixed-methods approach, this study combines quantitative analysis of customer data with qualitative interviews with marketing professionals and customers. Data were analyzed to assess the relationship between personalized marketing, customer engagement, and CLV. The findings reveal that personalized marketing significantly enhances customer engagement, leading to higher satisfaction and loyalty. However, challenges such as data privacy concerns and implementation costs can hinder its effectiveness. The study concludes that businesses must balance personalization with ethical data practices to maximize the impact of personalized marketing on CLV. This research contributes to the discourse on marketing strategy by providing practical recommendations for businesses to enhance customer relationships and drive long-term profitability through personalized marketing.
Technology Strategies in Health Promotion: Preventive Lifestyle Interventions to Reduce the Burden of Disease Ridwan, Eka Sari; Ahmad, Omar; Ali, Zainab
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 1 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i1.1905

Abstract

The global burden of disease, driven largely by preventable lifestyle factors such as poor diet, physical inactivity, and smoking, continues to strain healthcare systems worldwide. In response, health promotion strategies incorporating technological innovations have gained prominence as effective tools for preventive interventions. This study explores various technology-based strategies in health promotion, focusing on their role in encouraging preventive lifestyle changes to reduce the incidence of chronic diseases. The research employs a systematic review methodology, analyzing data from 40 peer-reviewed studies that evaluate the effectiveness of digital interventions such as mobile health apps, telemedicine, and wearable devices in promoting healthy behaviors. The findings indicate that technology-based interventions significantly improve health outcomes by increasing physical activity, enhancing dietary habits, and reducing smoking rates. Additionally, these interventions are shown to be highly effective in engaging populations that may have limited access to traditional healthcare services. The study concludes that technology-based health promotion strategies offer scalable, cost-effective solutions to reducing the burden of disease. However, challenges remain in ensuring equitable access and addressing concerns related to data privacy and security. The research underscores the importance of integrating technological tools into public health strategies to drive long-term improvements in population health.
Development of Hybrid Quantum Algorithm for Investment Portfolio Optimization Malik, Fatima; Iqbal, Kiran; Ali, Zainab
Journal of Tecnologia Quantica Vol. 1 No. 5 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v1i5.1686

Abstract

The background of this research focuses on the challenges of investment portfolio optimization, which often requires long computing time and high complexity, especially with many assets that must be analyzed. The use of quantum algorithms for investment optimization promises a faster and more efficient solution. The purpose of this study is to develop a hybrid quantum algorithm that can combine quantum and classical computing methods to improve portfolio optimization performance. The research method used is an experiment by testing a combination of quantum algorithms (such as variational quantum eigensolver, VQE) and classical algorithms to solve portfolio optimization problems using historical market data. The results show that the hybrid quantum algorithm successfully reduces computational time and improves accuracy in choosing the optimal asset combination, by minimizing risk and maximizing portfolio returns. The conclusion of this study is that the hybrid approach has great potential in overcoming the limitations that exist in pure quantum algorithms and can be effectively applied in investment portfolio optimization. Further research is needed to test these algorithms on a larger scale and with more dynamic market data.
Mathematical Physics and the Study of Complex Quantum Systems Batubara, Ana Uzla; Ali, Zainab; Vandika, Arnes Yuli
Research of Scientia Naturalis Vol. 1 No. 6 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v1i6.1585

Abstract

The study of complex quantum systems is a fundamental aspect of modern physics, providing insights into the behavior of matter at microscopic scales. Mathematical physics plays a crucial role in developing the theoretical frameworks necessary for understanding these systems, yet challenges remain in applying these concepts to real-world scenarios. This research aims to investigate the application of mathematical techniques in analyzing complex quantum systems. The focus is on identifying effective mathematical models and methods that can enhance our understanding of quantum phenomena. A comprehensive literature review was conducted, analyzing various mathematical approaches utilized in quantum mechanics, including perturbation theory, group theory, and numerical simulations. Case studies were examined to illustrate the successful application of these methods in real-world quantum systems. Findings indicate that advanced mathematical techniques significantly improve the modeling and analysis of complex quantum systems. The application of perturbation theory and numerical simulations provided deeper insights into system behaviors, while group theory facilitated a better understanding of symmetry properties. This research highlights the indispensable role of mathematical physics in the study of complex quantum systems. By emphasizing the integration of mathematical techniques, the study contributes to the advancement of theoretical physics and offers pathways for future research in quantum mechanics.