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All Journal Journal of Computer Science Application and Engineering Jurnal Sistem Informasi dan Teknik Informatika (JAFOTIK)
Amirah
Lentera Ilmu Publisher
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Other

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From Algorithms to Cures: AI's Impact on Drug Discovery Fitrah Karimah; Amirah
Journal of Computer Science Application and Engineering (JOSAPEN) Vol. 1 No. 2 (2023): JOSAPEN - July
Publisher : PT. Lentera Ilmu Publisher

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Abstract

This study explores the paradigm-shifting fusion of artificial intelligence (AI) and pharmaceuticals, heralding a new era of innovation in drug development. AI's transformative potential revolutionizes the traditionally arduous drug discovery process by seamlessly assimilating vast data volumes encompassing molecular structures, genetics, and disease pathways. This synergy expedites the identification of potential drug candidates with heightened precision and efficiency, propelling breakthrough treatments. The exploration navigates through AI-driven computational models, showcasing their role in expediting drug validation and optimization. AI's iterative learning enhances predictive capabilities, forecasting medication efficacy and safety profiles, thereby minimizing clinical trial risks and boosting success rates. Beyond acceleration, AI reshapes drug development strategies toward personalized medicine. Analyzing expansive patient datasets, AI tailors treatments based on genetic variations and disease characteristics, promising optimized therapeutic outcomes and minimized adverse effects, marking a departure from traditional healthcare approaches. The methodology employed various research techniques, including literature reviews, data collection, surveys, case studies, synthesis, and recommendations, offering comprehensive insights into AI's impact on drug discovery. In conclusion, the study emphasized AI's transformative potential in revolutionizing drug discovery, advocating for continued exploration and integration to optimize pharmaceutical research and development practices.
Leveraging Open Data with Machine Learning Algorithms Amirah; Fitrah Karimah
Jurnal Sistem Informasi dan Teknik Informatika (JAFOTIK) Vol. 1 No. 2 (2023): JAFOTIK - August
Publisher : PT. Lentera Ilmu Publisher

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In the evolving landscape of technology, the amalgamation of open data and machine learning stands as a powerful catalyst for innovation. This study explores the dynamic synergy between these domains, where open data's accessibility and transparency converge with machine learning's pattern recognition and predictive capabilities. The fusion holds immense promise across diverse sectors, from healthcare to finance, urban planning, and environmental science. By leveraging advanced algorithms on openly available information, organizations can gain unprecedented insights into trends, correlations, and anomalies, fostering a culture of innovation. The methodology involves a comprehensive literature review, knowledge enrichment, case studies, and conclusion, providing a systematic approach to understanding the intersection of open data and machine learning. The results showcase practical applications in predictive policing, healthcare resource allocation, smart traffic management, and more. Each application is supported by relevant machine learning algorithms, emphasizing their role in addressing complex challenges. The study culminates with a simplified example of predictive policing using a Support Vector Machine (SVM) algorithm, showcasing its pseudocode and decision function equation. This example illustrates how machine learning can predict crime occurrences based on patrol data and historical crime rates. Overall, this fusion marks a pivotal chapter in technological progress and societal advancement.
Co-Authors Fitrah Karimah