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All Journal Technomedia Journal ADI Bisnis Digital Interdisiplin (ABDI Jurnal) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi International Transactions on Education Technology (ITEE) International Transactions on Artificial Intelligence (ITALIC) Journal of Computer Science and Technology Application JOT AI, Innovation, and Resilience for the Environment Journal
Kamal Arif Al-Farouqi
Eduaward Incorporation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Video Storytelling as an Effective Strategy for College Brand Awareness Rilla Gantino; Desy Apriani; Fanani Islamia Ningrum; Rifqi Fahrudin; Kamal Arif Al-Farouqi; Bintang Nanda Henry
ADI Bisnis Digital Interdisiplin Jurnal Vol 6 No 2 (2025): ADI Bisnis Digital Interdisiplin (ABDI Jurnal)
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/abdi.v6i2.1303

Abstract

As digital threats to privacy and data integrity continue to rise, cybersecurity has become a critical issue in the business and financial sectors. However, existing risk mitigation strategies tend to focus primarily on technical aspects, often overlooking the ethical dimensions that are vital for governance and decision-making, especially in the development and implementation of emerging technologies such as Artificial Intelligence (AI). This study aims to explore the role of ethical principles in cybersecurity risk mitigation through a Systematic Literature Review (SLR). A total of eleven relevant articles were analyzed using the SALSA framework (Search, Appraisal, Literature Systems, Analysis). The findings indicate that ethical values such as transparency, accountability, fairness, and compliance with regulations play a significant role in enhancing the effectiveness of cybersecurity strategies. Key challenges identified include the absence of global ethical standards, limited human resources with digital ethics expertise, and ethical dilemmas in the use of AI. This review underscores the necessity of integrating ethical values into organizational policies, technologies, and cultures to establish more sustainable and trustworthy cybersecurity systems.
Efficient Machine Learning Acceleration with Randomized Linear Algebra for Big Data Dwi Cahyono; Apriani Sijabat; Kamal Arif Al-Farouqi
CORISINTA Vol 3 No 1 (2026): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/v3i1.163

Abstract

The rapid growth of big data has significantly increased the computational complexity of machine learning models, particularly due to intensive linear algebra operations that limit scalability and efficiency. This study aims to investigate the effectiveness of Randomized Linear Algebra (RLA) as an acceleration strategy for machine learning in large scale data environments. The research adopts an experimental methodology by integrating randomized techniques such as matrix sketching and random projection into standard machine learning pipelines and evaluating their performance against deterministic baseline approaches. Experiments are conducted on large dimensional datasets using multiple machine learning models, with performance assessed in terms of computational time, memory usage, model accuracy, and scalability. The results demonstrate that the proposed RLA based approach substantially reduces computational cost and memory consumption while maintaining comparable predictive accuracy to conventional methods. These findings indicate that randomized techniques provide an effective trade off between efficiency and accuracy, enabling scalable machine learning for big data applications. In conclusion, this study contributes to the advancement of efficient Artificial Intelligence (AI) systems by demonstrating that RLA can serve as a practical and scalable solution for accelerating machine learning computations in big data contexts, aligning with the growing demand for resource efficient and high performance AI infrastructures.
Emerging Educational Technologies and Their Influence on Preschool Learning Outcomes Annisa Ardien; Novena Ulita; Kamal Arif Al-Farouqi; Solahudin
Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Vol 4 No 2 (2026): March
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/mentari.v4i2.1047

Abstract

This study examines the influence of emerging educational technologies on preschool learning outcomes amid the increasing integration of digital tools such as educational applications, interactive games, and multimedia based platforms in early childhood education. Using a quantitative approach with a quasi experimental design, the study involved 167 preschool students who participated in technology-enhanced learning activities over a defined instructional period. Data were collected through structured observations, standardized assessments of learning outcomes, and teacher evaluations to comprehensively measure cognitive, social, and emotional development. The findings indicate that the use of emerging educational technologies has a statistically significant positive effect on preschool learning outcomes, particularly in improving student engagement, foundational literacy skills, problem-solving abilities, and cooperative behaviors compared to traditional instructional methods. In addition, teachers reported better classroom interaction, increased instructional efficiency, improved student participation, and more effective learning management when digital tools were implemented appropriately. These results suggest that the integration of technology not only enhances academic related skills but also supports broader developmental aspects of young learners. Therefore, the study highlights the importance of thoughtful and well structured implementation of educational technologies to maximize their benefits in early childhood education settings, ensuring sustainable, inclusive, and developmentally appropriate learning experiences.
SEO Dimensions and AI-Assisted Predictive Scoring for Digital Business Sales Performance in Indonesia Muchtadin Muchtadin; Michael Surya Gunawan; Dwi Safarina; Kamal Arif Al-Farouqi
International Transactions on Artificial Intelligence Vol. 4 No. 2 (2026): May
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v4i2.1093

Abstract

The intensification of digital commerce competition has elevated Search Engine Optimization (SEO) into a strategically important yet empirically underexplored determinant of sales performance, particularly within Indonesia’s rapidly expanding e-commerce ecosystem, where organic search drives over 64% of commercial platform traffic. This study examines the influence of three core SEO dimensions on page optimization, off-page optimization, and technical SEO on digital business sales performance, measured through website traffic growth, customer conversion rates, and revenue improvement. A quantitative explanatory design was applied using primary data from structured question naires administered to 120 digital business owners and e-commerce managers in Indonesia, cross-validated with secondary Google Analytics records over a twelve-month observation window. Multiple linear regression was conducted after validity, reliability, normality, multicollinearity, and heteroscedasticity tests. An AI-assisted Predictive SEO Performance Scoring (PSPS) model was also developed as a weighted composite function based on standardized regression coefficients to simulate performance trajectories across three SEO deployment scenarios. All three SEO dimensions showed statistically significant positive effects on sales performance (p < 0.05), with on-page SEO recording the strongest coefficient (β = 0.342), followed by technical SEO (β = 0.318) and off-page SEO (β = 0.291). The model explained 68% of performance variance (R2 = 0.68). PSPS scenario analysis showed that comprehensive SEO adoption produced an 83.5% relative performance improvement over minimal deployment. These findings position SEO as a core strategic investment aligned with Indonesia’s Making Indonesia 4.0 agenda and SDGs 8, 9, and 10.
Business Intelligence Implementation to Support Data Driven Strategic Decision Making in Digital Organizations Tessa Handra; Agung Rizky; Mungkap Mangapul Siahaan; Steven Harazaki Lase; Kamal Arif Al-Farouqi
Technomedia Journal Vol 11 No 1 (2026): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v11i1.2640

Abstract

Digital transformation has encouraged organizations to generate large volumes of data that must be managed effectively to support strategic decision-making. Business Intelligence has become a solution for integrating, analyzing, and presenting data into valuable information. This study aims to analyze the implementation of Business Intelligence in digital organizations, its role in supporting data-driven strategic decision-making, as well as the benefits and challenges of its implementation. This study used a qualitative method with a literature review approach by examining journals, scientific articles, and other academic publications related to the research topic. The data were analyzed using descriptive qualitative analysis. The results show that the implementation of BI through data warehouses, dashboards, reporting systems, and data analytics can improve operational efficiency, accelerate access to information, and support performance monitoring and business trend analysis more effectively. BI also supports faster and more accurate data-driven decision-making. Business Intelligence plays an important role in supporting strategic data-driven decision-making in digital organizations. However, its implementation still faces challenges related to data quality, information security, limited human resource competencies, and high technology implementation costs.
Ethical and Inclusive Design of AI Care Agents for People with Disabilities Vivi Meilinda; Umi Narimawati; Thomas Sumarsan Goh; Irene Apriani Widjaya; Kamal Arif Al-Farouqi
Journal of Orange Technology Vol. 2 No. 2 (2026): April
Publisher : Sinar Mentari Sundara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68012/jot.v2i2.70

Abstract

The increasing use of Artificial Intelligence (AI) in care services offers significant potential to improve the quality of life for people with disabilities, while also raising important ethical and inclusivity concerns. This study examines the ethical and inclusive design of AI care agents, emphasizing human-centered principles that support autonomy, dignity, and emotional well-being. This study employs a quantitative research approach using a cross-sectional survey design. Data were collected from individuals with diverse physical, sensory, and cognitive disabilities who have experience interacting with AI care agents. Measurement instruments were adapted from established ethical AI, inclusive design, and technology acceptance frameworks. Humanistic well-being was assessed using the WHO-5 Well-Being Index. The data were analyzed using Structural Equation Modeling (SEM) to examine the relationships between ethical AI design, inclusive features, user trust, technology acceptance, emotional support, and well-being outcomes. The findings indicate that ethical AI design significantly enhances user trust and perceived emotional support, while inclusive design features positively influence technology acceptance and emotional engagement. User trust, technology acceptance, and emotional support significantly contribute to humanistic well-being, with emotional support emerging as the strongest predictor. This study contributes a quantitative empirical model demonstrating how ethical and inclusive AI design principles translate into measurable well-being outcomes for people with disabilities. The findings highlight the importance of integrating humanistic values into AI care agent development to ensure equitable, responsible, and sustainable digital care innovation.
Blockchain Applications for Transparency in the Insurance Industry Chandra Lukita; Harry Agustian; Kamal Arif Al-Farouqi; Fazri Arkiman
AI, Innovation, and Resilience for the Environment (AIR) Vol. 1 No. 1 (2026): AI, Innovation, and Resilience for the Environment (AIR) Journal
Publisher : Sinar Mentari Sundara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68012/air.v1i1.122

Abstract

Transparency has become a critical pillar for trust in the insurance industry, yet traditional systems remain plagued by opaque claim procedures, high fraud rates, and inefficiencies caused by centralized databases. This study aims to analyze how blockchain-based mechanisms can address key pain points in claims processing, fraud detection, and data integrity. Adopting a conceptual and qualitative research approach, the methodology synthesizes findings from academic publications, industry reports, and real-world implementations to evaluate blockchain's contribution across four dimensions: process transparency, operational efficiency, trust, and regulatory compliance. The results indicate that core blockchain attributes—such as smart contracts and immutable ledgers significantly accelerate claim settlements, reduce information asymmetry, and enable real time behavior tracking through technologies like the Internet of Vehicles (IoV). It is concluded that while challenges regarding privacy and regulatory fragmentation persist, blockchain offers a paradigm shift toward a more transparent, efficient, and trustworthy insurance ecosystem by realigning economic incentives between insurers and policyholders.
Designing Educational Information Systems to Optimize Learning Factory Operations Naufal Fadillah Akbar; Nur Azizah; Kamal Arif Al-Farouqi; Irene Apriani Widjaya; Ruli Supriati
International Transactions on Education Technology (ITEE) Vol. 4 No. 1 (2025): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v4i1.969

Abstract

Interdisciplinary teamwork within the learning factory framework has emerged as an effective approach to bridging theoretical knowledge and practical inno- vation, encouraging students from diverse academic backgrounds to collaborate and solve complex real world problems creatively. This educational model pro- motes experiential learning, yet the specific mechanisms through which inter- disciplinary collaboration enhances creativity and innovation remain underex- plored. This study aims to investigate how teamwork across multiple disciplines fosters innovation and creativity in learning factory projects and to identify the factors that facilitate or hinder this process. Using a qualitative case study design, data were collected through semi structured interviews, direct observa- tions, and project documentation involving students and instructors from engi- neering, design, and business programs participating in interdisciplinary learn- ing factory initiatives. The data were analyzed thematically to identify key pat- terns of collaboration, communication, and idea generation. The findings reveal that interdisciplinary teamwork significantly stimulates creative problem solv- ing by integrating diverse perspectives, promoting mutual learning, and creating an environment that values experimentation and iteration. However, challenges such as disciplinary boundaries, communication gaps, and differing work cul- tures occasionally impede the collaborative process. The study concludes that effective facilitation, open communication, and reflective practices are crucial for maximizing innovation and creativity in interdisciplinary learning factory teams. These insights highlight the importance of designing structured yet flexi- ble learning environments that encourage knowledge integration, creative think- ing, and cross disciplinary synergy to prepare students for complex, innovation driven professional contexts.
Co-Authors Agung Rizky Annisa Ardien Apriani Sijabat Bintang Nanda Henry Chandra Lukita Desy Apriani Dwi Cahyono Dwi Safarina Fanani Islamia Ningrum Fazri Arkiman Harry Agustian Irene Apriani Widjaya Irene Apriani Widjaya Michael Surya Gunawan Muchtadin Muchtadin Mungkap Mangapul Siahaan Naufal Fadillah Akbar Novena Ulita Nur Azizah Rifqi Fahrudin Ruli Supriati, Ruli Solahudin Steven Harazaki Lase Tessa Handra Thomas Sumarsan Goh Umi Narimawati Vivi Meilinda