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All Journal JOURNAL OF ICT APLICATIONS AND SYSTEM TRIMAS: Jurnal Inovasi dan Pengabdian Kepada Masyarakat DIGITAL BUSINESS INSIGHTS JOURNAL Technema: Journal of Intelligent Engineering and Computing
Irwandi Rizki Putra
Universitas Riau Indonesia
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Social Sciences

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Enhanced Classification of Brain MRI Images for Tumor Detection Using Transfer Learning and Grad-CAM-Based Explainable Convolutional Neural Network (CNN) Putra, Irwandi Rizki; Zulrahmadi; Andri Swandi; Yulia; Tasya Destria Putri
Journal of ICT Applications System Vol 4 No 2 (2025): Journal of ICT Aplications and System
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56313/jictas.v4i2.454

Abstract

Accurate and explainable classification of brain Magnetic Resonance Imaging (MRI) is crucial for the early detection and treatment of brain tumors. This study introduces an enhanced deep learning framework that integrates transfer learning with Grad-CAM-based explainable Convolutional Neural Network (CNN) for tumor classification. The proposed approach utilizes a fine-tuned EfficientNet-B0 architecture with an optimized preprocessing pipeline consisting of Contrast Limited Adaptive Histogram Equalization (CLAHE), normalization, and multi-variant augmentation (rotation, flipping, and zoom). The model was trained on a publicly available brain MRI dataset comprising 3,000 images classified into four categories: glioma, meningioma, pituitary tumor, and non-tumor. Evaluation metrics include accuracy, precision, recall, F1-score, and AUC. Experimental results demonstrate that the proposed model achieves an accuracy of 94.2% and an AUC of 0.965, outperforming baseline CNN models by a significant margin. The use of Grad-CAM visualization provides interpretability by localizing tumor regions within MRI scans, thereby increasing the model’s clinical transparency. This study highlights the potential of explainable deep learning models to enhance diagnostic reliability in automated brain tumor detection systems.
ANALISIS STRATEGI PEMASARAN TIKTOK SHOP DI ERA DIGITAL Juwita Astuti; Rahimah Safitri; Dewi Santika Ulandari; Sinta Wulandari; Irwandi Rizki Putra
Digital Business Insights Journal Vol 2 No 1 (2026): DIGITAL BUSINESS INSIGHTS JOURNAL
Publisher : Fakultas Ekonomi dan Bisnis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/bidi.v2i1.4967

Abstract

This study investigates the rising competition in e-commerce and the rapid growth of TikTok Shop as an interactive digital marketing platform. The primary research problem concerns how TikTok Shop’s live streaming feature, creative content, and influencer marketing affect consumers’ purchase intention for the Glad2Glow brand. The study aims to analyze the effectiveness of these strategies in building trust and improving purchasing decisions. A descriptive qualitative method was employed using literature review and content analysis based on secondary digital data. The findings reveal that live streaming is the most influential variable in increasing purchase intention, followed by creative content and influencer collaboration, which enhance brand credibility. Promotional tactics such as flash sales and real-time product demonstrations significantly increased sales conversion. The study recommends that SMEs continue optimizing live commerce features and strengthen authentic content to improve competitiveness in the digital marketplace.
Edge Intelligence in Smart Manufacturing Ecosystems Irwandi Rizki Putra; Anjela Karunia Amalia; Krisna Widi Nugraha; Tuti Susilawati; Hadi Jayusman
Technema: Journal of Intelligent Engineering and Computing Vol. 1 No. 2 (2026): : June: Technema: Journal of Intelligent Engineering and Computing
Publisher : CV SCRIPTA INTELEKTUAL MANDIRI

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Abstract

The rapid evolution of smart manufacturing ecosystems has intensified the need for intelligent architectures capable of supporting real-time decision-making, operational resilience, and sustainable industrial performance. This study investigates the effectiveness of Edge Intelligence within smart manufacturing environments through an empirical system-design and experimental validation approach. A three-layer architecture consisting of the Industrial Internet of Things layer, the edge intelligence layer, and the cloud orchestration layer was developed and evaluated under predictive maintenance, production scheduling, and anomaly detection scenarios. Performance assessment employed metrics including inference latency, response time, bandwidth consumption, prediction accuracy, throughput, resource utilization, reliability, resilience, and energy efficiency. The experimental results demonstrate that edge-enabled intelligence significantly improves manufacturing performance by reducing latency and communication overhead while increasing operational responsiveness, decision consistency, throughput, and system reliability. The architecture also enhances adaptive decision-making capabilities, strengthens human-machine collaboration, improves cybersecurity resilience, and contributes to environmental sustainability through more efficient resource utilization and reduced carbon emissions. The findings establish Edge Intelligence as a strategic ecosystem capability that enables resilient, adaptive, human-centric, and sustainable manufacturing systems aligned with the emerging objectives of Industry 5.0.  
Peningkatan Literasi Artificial Intelligence dan Etika Digital bagi Siswa Madrasah Aliyah Al Syahni dalam Menghadapi Era Society 5.0 Irwandi Rizki Putra; Muhlisahtun Niswah; Indrayani; Iriene Putri Mulyadi; Mesy Yulandari
TRIMAS: Jurnal Inovasi dan Pengabdian Kepada Masyarakat Vol. 5 No. 2 (2025): Trimas: Jurnal Inovasi dan Pengabdian Kepada Masyarakat
Publisher : Indra Institute Research & Publication

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Abstract

This study aims to improve Artificial Intelligence (AI) literacy and digital ethics awareness among students at Madrasah Aliyah Al Syahni, Indragiri Hilir, in order to prepare them to face the dynamics of the Society 5.0 Era. The method used is Action Research with a participatory approach involving the cycle of planning, implementation, evaluation, and reflection. The research subjects consisted of students and teachers at Madrasah Aliyah Al Syahni, which currently still uses a manual data management system. Data collection instruments included a Likert scale questionnaire, in-depth interviews, and classroom observations. The results of the study showed a significant increase in students' AI literacy, especially in the cognitive (+36.7%) and affective (+38.7%) aspects, after the implementation of AI tools such as Socratic and ChatGPT. The findings also indicate that strengthening digital ethics based on Islamic values ​​and Maqasid al-Shari'ah is very effective in mitigating the risk of plagiarism and technology dependency. In conclusion, the integration of structured AI with a foundation of digital ethics can create an adaptive, responsive, and humanistic learning ecosystem in accordance with the vision of Society 5.0.
ANALISIS STRATEGI PEMASARAN TIKTOK SHOP DI ERA DIGITAL Juwita Astuti; Rahimah Safitri; Dewi Santika Ulandari; Sinta Wulandari; Irwandi Rizki Putra
Digital Business Insights Journal Vol 2 No 1 (2026): DIGITAL BUSINESS INSIGHTS JOURNAL
Publisher : Fakultas Ekonomi dan Bisnis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/bidi.v2i1.4967

Abstract

This study investigates the rising competition in e-commerce and the rapid growth of TikTok Shop as an interactive digital marketing platform. The primary research problem concerns how TikTok Shop’s live streaming feature, creative content, and influencer marketing affect consumers’ purchase intention for the Glad2Glow brand. The study aims to analyze the effectiveness of these strategies in building trust and improving purchasing decisions. A descriptive qualitative method was employed using literature review and content analysis based on secondary digital data. The findings reveal that live streaming is the most influential variable in increasing purchase intention, followed by creative content and influencer collaboration, which enhance brand credibility. Promotional tactics such as flash sales and real-time product demonstrations significantly increased sales conversion. The study recommends that SMEs continue optimizing live commerce features and strengthen authentic content to improve competitiveness in the digital marketplace.
Co-Authors Andri Swandi Anjela Karunia Amalia Dewi Santika Ulandari Hadi Jayusman Indrayani Iriene Putri Mulyadi Juwita Astuti Juwita Astuti Krisna Widi Nugraha Mesy Yulandari Muh. Rasyid Ridha Muhlisahtun Niswah Rahimah Safitri Sinta Wulandari Tasya Destria Putri Tuti Susilawati yulia Zulrahmadi