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All Journal Gender Equality: Internasional Journal of Child and Gender Studies PROCURATIO: Jurnal Manajemen dan Bisnis Journal of Computing Theories and Applications Journal of Future Artificial Intelligence and Technologies AURORA: Journal of Emerging Business Paradigms
Fuzail, Muhammad
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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Enhanced Diagnosis of Skin Cancer from Dermoscopic Images Using Alignment Optimized Convolutional Neural Networks and Grey Wolf Optimization Mazhar, Faheem; Aslam, Naeem; Naeem, Ahmad; Ahmad, Haroon; Fuzail, Muhammad; Imran, Muhammad
Journal of Computing Theories and Applications Vol. 2 No. 3 (2025): JCTA 2(3) 2025
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.11954

Abstract

Skin cancer (SC) is a highly serious kind of cancer that, if not addressed swiftly, might result in the patient’s demise. Early detection of this condition allows for more effective therapy and prevents disease development. Deep Learning (DL) approaches may be used as an effective and efficient tool for SC detection (SCD). Several DL-based algorithms for automated SCD have been reported. However, more efficient models are needed to improve accuracy. As a result, this paper introduces a new strategy for SCD based on Grey Wolf optimization (GWO) methodologies and CNN. The proposed methodology has four stages: preprocessing, segmentation, feature extraction, and classification. The proposed method utilizes a Convolutional Neural Network (CNN) to extract features from Regions of Interest (ROIs). CNN is employed for feature categorization, whereas the GWO approach enhances accuracy by refining edge detection and segmentation. This technique utilizes a probabilistic model to accelerate the convergence of the GWO algorithm. Employing the GWO model to optimize the structure and weight vectors of CNNs can enhance diagnostic accuracy by a minimum of 5%, based on evaluation outcomes. The application of the proposed strategy and its performance comparison with other methods indicate that the proposed method with GWO predicted SC with an average accuracy of 95.11% and without GWO an Accuracy of 92.66%, respectively, enhancing accuracy by a minimum of 2.5% when we train our model with GWO.
Unraveling sexual harassment's effect on employee performance: Motivation, stress, and satisfaction as key mediators Sangadji, Suwandi S.; Sudarnice, Sudarnice; Eliyana, Anis; Fuzail, Muhammad
INTERNATIONAL JOURNAL OF CHILD AND GENDER STUDIES Vol 11, No 1 (2025)
Publisher : Universitas Islam Negeri Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/equality.v11i1.26285

Abstract

Sexual harassment has emerged as a major concern in women's workplaces and has significant implications for female employees' performance. This study aims to assess the effect of sexual harassment on the performance of Sales Promotion Girls (SPG) by considering motivation, job stress, and job satisfaction as mediating factors. Using a survey-based quantitative method, data were collected from 260 respondents from PT. Hanjaya Mandala Sampoerna and analyzed using Structural Equation Modeling (SEM) with Smart PLS.  The findings indicate that sexual harassment significantly affects job stress, work motivation, and job satisfaction among SPG. Moreover, job stress has a positive and significant effect on both work motivation and SPG performance. Sexual harassment was found to indirectly affect SPG performance through the mediating roles of job stress and work motivation. Furthermore, job satisfaction also mediates the relationship between sexual harassment and SPG performance. This study provides valuable insights for improving employee performance, particularly for SPG who experience sexual harassment. A better understanding of its impact enables companies to implement appropriate measures to reduce job stress and enhance SPG motivation, ultimately leading to increased job satisfaction. This not only fosters a safer and more positive work environment for employees but also contributes to overall productivity and SPG performance. Additionally, companies can take concrete steps to proactively prevent and address workplace sexual harassment, ensuring both the well-being and optimal performance of their SPG employees.
Mapping Unseen Connections: Graph Clustering to Expose User Interaction Patterns Ahmad, Haroon; Sajid, Muhammad; Mazhar, Faheem; Fuzail, Muhammad
Journal of Future Artificial Intelligence and Technologies Vol. 1 No. 4 (2025): March 2025
Publisher : Future Techno Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/faith.3048-3719-77

Abstract

Expanding extensive and intricate social networks has required sophisticated community detection techniques. This study presents an innovative hybrid methodology that utilizes node space similarity and local knowledge to enhance community identification. Node space similarity is defined by integrating eigenvector centrality (EC), which quantifies a node’s influence inside the network, with proximity metrics, such as closeness, to evaluate the connectivity between nodes. This enables us to identify cohorts of individuals with analogous influence and connectivity. We use local knowledge by concentrating on these pivotal nodes' direct connections and attributes, allowing the technique to broaden community discovery (CD) outward effectively. Our five-phase methodology, grounded in an iterative seed expansion algorithm, commences with identifying highly central nodes and progressively develops communities by integrating nodes exhibiting high similarity and local connectivity. The method incorporates graph statistical inference and embedding features to improve accuracy and capture extensive network patterns. This integrated approach facilitates the precise and effective identification of communities within extensive social networks, exceeding the constraints of conventional techniques. This research attained a modularity of 95.05% on the DBLP dataset and 94.50% on the Amazon dataset. This study achieved a Normalized Mutual Information (NMI) of 91.80% on the DBLP dataset, 92.50% on the Amazon dataset, and 90.43% on the football dataset, demonstrating superior performance relative to previous methodologies. The findings indicate that the hybrid method outperforms other recognized methods in large-scale graphs, showcasing notable robustness and efficiency.
Consumer Acceptance of Eco-Friendly Products in Pakistan: A Qualitative Study Based on Consumer Behavior Theory Fuzail, Muhammad
Aurora: Journal of Emerging Business Paradigms Vol. 2 No. 1 (2025): June
Publisher : PT. Sangadji Media Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62394/aurora.v2i1.186

Abstract

This study investigates the factors influencing consumer acceptance of eco-friendly products in Pakistan, using consumer behavior theory as a conceptual framework. By applying a qualitative research design, in-depth interviews were conducted with 18 participants to uncover the underlying psychological, social, and situational factors that drive or hinder sustainable consumption. The study finds that environmental awareness, attitudinal beliefs, and social norms significantly shape consumer intentions, while behavioral control barriers such as high product costs, limited accessibility, and inconvenience remain the primary inhibitors. Notably, social influence from reference groups, including family and peers, was identified as a powerful force, with younger, urban consumers showing greater eco-friendly preferences due to social pressure and media exposure. Perceived behavioral control—influenced by affordability, convenience, and availability—emerged as a critical determinant of consumer behavior. The findings reveal that while consumers express positive attitudes towards green products, practical challenges prevent the widespread adoption of eco-friendly alternatives. This research contributes to the literature by offering novel insights into the unique contextual factors influencing green consumer behavior in a developing country like Pakistan. It emphasizes the importance of tailored marketing strategies and policy interventions to address barriers and promote sustainable consumption. For marketers and policymakers, the study suggests that addressing cost concerns, improving product availability, and fostering trust in environmental claims can facilitate the adoption of eco-friendly products. Future research could explore the longitudinal impact of such interventions.
Emerging Business Paradigms in the Digital and Agribusiness Sectors: Integrative Insights from Consumer Behavior, Technological Innovation, and Sustainable Development Fuzail, Muhammad; Shareef, Shahdat
PROCURATIO: Jurnal Manajemen & Bisnis Vol. 4 No. 1 (2025): January - June
Publisher : PT. Sangadji Media Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62394/projmb.v4i1.183

Abstract

Purpose – This study aims to explore and synthesize emerging business paradigms in the digital and agribusiness sectors by examining how consumer behavior, technological innovation, and sustainability converge to shape strategic business practices. Grounded in both theoretical and practical contexts, the research addresses the need for more integrated, adaptive approaches that respond to the rapidly evolving market and societal demands in digital economies and agri-based systems. Design/method/approach – The research adopts a qualitative multiple-case study approach, combining a systematic review of recent literature with semi-structured interviews involving practitioners from digital and agribusiness sectors in Southeast Asia. Data were analyzed thematically using triangulation to identify cross-cutting patterns, strategic insights, and emergent trends that highlight integrative business dynamics. Findings – The study finds a paradigmatic shift toward value co-creation with consumers, the strategic use of immersive technologies for emotional branding, the growing importance of localized innovation strategies, and the systemic integration of sustainability practices. Interviewees emphasize agility, empathy, and collaboration as key competencies in navigating the shift from transactional to relational value models. These insights reinforce the need for ecosystem-based approaches and socially embedded technological adoption. Implications – The findings offer valuable contributions to both theory and practice by illustrating how socio-technical systems thinking and glocalization strategies can guide business transformation. For practitioners, the research underscores the importance of aligning innovation with local context, embedding sustainability into the core of strategy, and fostering consumer-driven engagement in both digital and agribusiness sectors. Novelty/Originality – This study contributes a novel cross-sectoral perspective by bridging digital and agribusiness insights through an integrative analytical lens. It fills a critical gap in literature by illustrating how business paradigms are evolving holistically, particularly in underexplored emerging markets, with practical implications for sustainable competitiveness.
Co-Authors Ahmad, Haroon Anis Eliyana Aslam, Naeem Dea Rizky Amalia Putri Mazhar, Faheem Muhammad Imran Naeem, Ahmad Rahmat Hidayat Sajid, Muhammad Shareef, Shahdat Sudarnice, Sudarnice Suwandi S. Sangadji Yunita, Andi