Garuda - Garba Rujukan Digital

Andik Prakasa Hadi

Universitas Sains Dan Teknologi Komputer

Author-ID : 1149519

Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Nursing Public Health Social Sciences Other

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Simulation Of A Trash Can Using Line Follower Based On Arduino Iqbal Hakim; Andik Prakasa Hadi
Journal of Technology Informatics and Engineering Vol 2 No 1 (2023): April : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v2i1.173

There is a lot of dirt scattered around the State Elementary School (SDN) 03 Purwoyoso, Semarang. The habit of elementary school children and their parents is that they often throw rubbish everywhere and are lazy about throwing away the rubbish. even though there are already rubbish bins provided at the school. Children like new things, especially those shaped like toys. Garbage is a nesting place for bacteria that can cause various diseases. Humans are blessed with five senses which help them detect various things that threaten their lives. However, in the modern world, various forms of threats emerge that are not detected by our five senses, namely various types of poisons made by humans themselves. More than 75,000 synthetic chemicals have been produced by humans in the last decades. Many of them have no color, taste and smell, but have the potential to cause health hazards. Based on the problems described, the author tries to make a trash can using an Arduino-based line follower as a micro controller. This trash can can walk to the desired student line in a certain area with control carried out by a calling mechanism using a recorded voice. And if the smell is strong, the Buzzer will sound, after the students throw away the trash , the Dot Matrix LED will light up the words Thank You. It is hoped that with this rubbish bin, it will make the rubbish bin more attractive so that children will throw rubbish in its place.

Simulation Of A Trash Can Using Line Follower Based On Arduino Iqbal Hakim; Andik Prakasa Hadi
Journal of Technology Informatics and Engineering Vol. 2 No. 1 (2023): April : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v2i1.173

There is a lot of dirt scattered around the State Elementary School (SDN) 03 Purwoyoso, Semarang. The habit of elementary school children and their parents is that they often throw rubbish everywhere and are lazy about throwing away the rubbish. even though there are already rubbish bins provided at the school. Children like new things, especially those shaped like toys. Garbage is a nesting place for bacteria that can cause various diseases. Humans are blessed with five senses which help them detect various things that threaten their lives. However, in the modern world, various forms of threats emerge that are not detected by our five senses, namely various types of poisons made by humans themselves. More than 75,000 synthetic chemicals have been produced by humans in the last decades. Many of them have no color, taste and smell, but have the potential to cause health hazards. Based on the problems described, the author tries to make a trash can using an Arduino-based line follower as a micro controller. This trash can can walk to the desired student line in a certain area with control carried out by a calling mechanism using a recorded voice. And if the smell is strong, the Buzzer will sound, after the students throw away the trash , the Dot Matrix LED will light up the words Thank You. It is hoped that with this rubbish bin, it will make the rubbish bin more attractive so that children will throw rubbish in its place.

The Enhancing Cybersecurity with AI Algorithms and Big Data Analytics: Challenges and Solutions Nugroho, Setiyo Adi; Sumaryanto, Sumaryanto; Hadi, Andik Prakasa
Journal of Technology Informatics and Engineering Vol. 3 No. 3 (2024): December (Special Issue: Big Data Analytics) | JTIE: Journal of Technology Info
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i3.200

As digital transformation accelerates across industries, cybersecurity faces escalating challenges due to increasingly sophisticated cyber threats. This study explores the integration of artificial intelligence (AI) algorithms and big data analytics to enhance cybersecurity systems, focusing on addressing data integration and interpretability issues. Employing a descriptive-qualitative methodology, the research analyzes literature, case studies, and secondary data to evaluate the effectiveness of AI and big data in detecting and mitigating cyber threats. Key findings reveal that deep learning algorithms, such as artificial neural networks, achieved an accuracy of 93% in anomaly detection, outperforming traditional rule-based approaches by 18%. Additionally, big data platforms like Spark demonstrated superior efficiency, processing 500 GB of data in 35 seconds compared to Hadoop’s 60 seconds. However, the study identifies challenges related to the interpretability of AI models and the complexity of integrating diverse datasets, which impede real-time threat detection. Periodic updates to AI training datasets were found to improve detection accuracy by up to 15%, emphasizing the importance of adaptive learning models. This research contributes to the field by proposing strategies to enhance system resilience, including adopting Explainable AI (XAI) for transparency and advanced data integration techniques. The findings underscore the potential of AI and big data to revolutionize cybersecurity, offering organizations a proactive approach to combating evolving cyber threats. Future studies should focus on sector-specific implementations and optimizing response mechanisms for comprehensive security frameworks.

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