Cognitech Informatics Journal of Reflections
Systematic Literature Review pada Penggunaan Deep Learning untuk Deteksi Dini Penyakit
Advances in artificial intelligence technology, particularly deep learning, have driven major transformations in early disease detection. With the ability to analyze large amounts of medical data, deep learning algorithms can accurately and efficiently identify complex patterns in medical images, electronic health records, and biological signals. This study is a systematic literature review that aims to summarize the latest developments in the use of deep learning for the early detection of various types of diseases. Based on a rigorous selection of 590 articles from four major databases, 10 studies were selected for in-depth analysis. The main findings show that deep learning has been successfully applied to the detection of lung, neurological, cardiovascular, and sleep disorders. Models such as CNN, RNN, and hybrid architectures show high performance in medical data-based classification and diagnosis. However, challenges arise, including the limited availability of high-quality data, computational complexity, and the need for clinical validation. The results of this study emphasize that the integration of deep learning technology into healthcare systems not only improves the accuracy and efficiency of diagnosis but also opens up great opportunities for predictive and personalized healthcare services. This research emphasizes the need to strengthen data infrastructure, multimodal approaches, and synergy between technology and medical personnel as the foundation for optimizing the role of deep learning in modern healthcare systems.
Copyright (c) 2026 Abdul Rahman, Riyayatsyah Riyayatsyah https://creativecommons.org/licenses/by-nc-sa/4.0
Analisis Sistem Rekomendasi Berbasis Machine Learning: Tinjauan Literatur Sistematis
This study is a systematic literature review that discusses the development of recommendation systems based on machine learning (ML) and deep learning (DL) in various domains, such as e-commerce, education, entertainment, and online content services. Recommendation systems play a crucial role in improving accuracy, relevance, and personalization by utilizing intelligent algorithms to analyze user preferences. Through an in-depth review of ten recent studies, this study identifies a variety of algorithmic approaches including collaborative filtering, content-based filtering, and hybrid methods. In addition, key challenges such as cold start issues, data scarcity, scalability, and user privacy are also reviewed. The findings show that deep learning is able to capture complex patterns and significantly improve recommendation performance. Evaluation of the recommendation system using metrics such as RMSE, MAE, F1-score, and R-squared is essential to ensure the effectiveness and sustainability of the model. This research emphasizes the importance of selecting algorithms that are appropriate to the characteristics of the domain and the needs of the user. The implications of this study are expected to be a guide for the development of ML and DL-based recommendation systems that are more adaptive, accurate, and user-centric in the future.
Copyright (c) 2026 Afifah Khaerani Aziz, Faza Alameka https://creativecommons.org/licenses/by-nc-sa/4.0
Analisis Perkembangan Teknologi Blockchain dalam Sistem Informasi: Studi Systematic Literature Review)
This study aims to systematically examine the latest findings regarding the implementation of blockchain technology in the context of information systems through a thematic approach. The results of the study show that blockchain has great potential in improving the security, transparency, and efficiency of information systems, especially through decentralization, traceability, and data retention features. This technology has been applied promisingly in the accounting, finance, and telecommunications sectors, with a significant contribution to improving the reliability of information systems. However, challenges such as scalability, interoperability, high adoption costs, and regulatory uncertainty remain major obstacles to its widespread implementation. To address this, a structured implementation strategy and close collaboration between technology developers, user institutions, and policymakers are needed. In addition, the integration of blockchain with cutting-edge technologies such as artificial intelligence (AI) and quantum computing is considered to be able to strengthen the security and effectiveness of information systems in the future. This study recommends that further research be focused on the development of integrative models across sectors, evaluation of cost efficiency, and the formulation of a strong legal and ethical framework. With a collaborative and multidisciplinary approach, blockchain has the potential to be a key foundation in supporting inclusive, adaptive, and sustainable digital transformation.
Copyright (c) 2026 Neng Wiwin, Fahrullah https://creativecommons.org/licenses/by-nc-sa/4.0
Evaluasi Penggunaan Teknologi Augmented Reality dalam Pendidikan: Sebuah Studi Literatur Reviews
This study aims to evaluate the use of Augmented Reality (AR) technology in education through a systematic literature study. AR is a technology that allows the integration of virtual objects into real environments, creating interactive, immersive, and contextual learning experiences. The study analyzed ten scientific articles obtained through reputable databases such as Scopus, PubMed, and Web of Science, with qualitative approaches and content analysis methods. The results show that the use of AR in learning significantly increases student motivation, engagement, and understanding, especially in subjects that require high visualization such as Biology and Chemistry. However, its implementation still faces various challenges, including limited infrastructure, lack of teacher training, high implementation costs, and availability of relevant content. In addition, the success of AR integration is also greatly influenced by pedagogical approaches and social factors such as user perception and institutional support. This study concludes that AR has great potential to transform the education system, as long as it is supported by inclusive policies, appropriate training strategies, and the development of a curriculum that is adaptive to technology. This research provides important insights for educators, technology developers, and policymakers to make optimal use of AR in order to create more engaging and meaningful 21st-century learning.
Copyright (c) 2026 Moch. Waris Laksana Agung, Rosmasari https://creativecommons.org/licenses/by-nc-sa/4.0
Keamanan Siber dalam Dunia IoT: Tinjauan Sistematis Literatur
The rapid development of the Internet of Things (IoT) has brought significant transformations in various sectors, but at the same time increases the complexity and risks of cybersecurity. Limited device resources, high levels of interconnectivity, and integration of advanced technologies such as artificial intelligence (AI), machine learning (ML), blockchain, and 5G networks make the IoT ecosystem vulnerable to various cyber threats, including privacy breaches, malware, and denial-of-service attacks. This study aims to comprehensively analyze the cybersecurity landscape in the IoT world through a systematic review of the literature. The method used refers to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines by searching the Scopus, Web of Science, ScienceDirect, and PubMed databases. Of the 470 articles identified, only 10 studies met the inclusion criteria and were analyzed in depth. The results of the study show that the main challenges of IoT security include the diversity of devices, weak authentication mechanisms, lack of security updates, and low user awareness. The solutions proposed in the literature include a holistic security approach, the application of security-by-design principles, the use of AI and ML for threat detection, and policy strengthening and cross-stakeholder collaboration. However, the effectiveness of existing solutions still faces technical and economic limitations. This research confirms the importance of a multidimensional and sustainable approach to building a secure, resilient, and trusted IoT ecosystem in the digital era.
Copyright (c) 2026 Sigit Nurcahyono, Haerullah https://creativecommons.org/licenses/by-nc-sa/4.0