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All Journal Gaung Informatika Jurnal Ilmiah Teknik Industri INFORMATIKA Aptisi Transactions on Technopreneurship (ATT) Jurnal Ilmiah Sinus Go Infotech: Jurnal Ilmiah STMIK AUB JICS : Journal Of International Community Service International Journal of Social and Education (INJOSEDU) International Journal of Advances in Artificial Intelligence and Machine Learning Prosiding Seminar Nasional Indonesia
Haryanto, Haryanto
Program Studi Sistem Komputer, Universitas Dharma AUB Surakarta
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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The Eye's Signature: Innovative Approaches to Iris Detection Pambudi, Dhidhi; Fadly, Fadly; Kurniawan, Muhammad Hafiz; Haryanto, Haryanto
International Journal of Advances in Artificial Intelligence and Machine Learning Vol. 2 No. 1 (2025): International Journal of Advances in Artificial Intelligence and Machine Learni
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijaaiml.v2i1.379

Abstract

This research aims to develop and evaluate a deep learning-based iris detection system using a specialized Convolutional Neural Network (CNN) architecture. The research methodology includes data set preprocessing, CNN model design, training using Adam optimization, as well as evaluation using accuracy, precision, recall, and F1 score metrics. The dataset used was obtained from Kaggle and preprocessed before being divided into training, validation, and testing sets. The CNN model consists of three convolutional layers with increasing filter sizes (32, 64, and 128), ReLU activation, batch normalization, and MaxPooling layers for efficient feature extraction, as well as dropout regularization to reduce overfitting. Experimental results show that the proposed model achieves a high classification accuracy of 97.33%, with robust performance against variations and noise in iris images. Comparative analysis with traditional iris recognition methods confirms the superiority of deep learning in handling challenges such as lighting changes and occlusions. Although the results are promising, challenges such as data bias and computational demands are still a concern. Future research will explore more advanced architectures as well as additional pre-processing techniques to improve the generalizability and effectiveness of the system in real-world applications.
User-Friendly Interface and Comprehensive Features for Hostel Management Kolan, Helini; Mungi, Keerthana; Somayajula, Lekhana; Achanta, Harshitha; Edulakanti, Vaishnavi; Haryanto, Haryanto
International Journal of Advances in Artificial Intelligence and Machine Learning Vol. 2 No. 3 (2025): International Journal of Advances in Artificial Intelligence and Machine Learni
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijaaiml.v2i3.456

Abstract

Background of study: Hostel administration in academic institutions has traditionally relied on manual processes such as paper-based record keeping, in-person registration, and ad-hoc maintenance communication. These fragmented practices often lead to inefficiencies, delays, miscommunication, and data inaccuracy. As student populations grow and operational demands increase, institutions require modernized systems that integrate automation, usability, and real-time information management to improve service delivery and resource allocation. However, existing solutions frequently lack comprehensive features, scalability, or user-centric design, indicating a clear gap in the availability of accessible and robust digital hostel management platforms.Aims: This study aims to design and implement a user-friendly, web-based Hostel Management System (HMS) that consolidates key administrative operations including student registration, room allocation, maintenance reporting, and occupancy tracking within a unified interface. The scope encompasses database design, workflow automation, interface usability, security provisions, and system evaluation through functional demonstrations.Methods: The system was developed following an Agile methodology, enabling iterative refinement based on user feedback. Dataset acquisition involved collecting student, room, facility, and maintenance information, followed by preprocessing steps such as data cleaning, normalization, and categorization to ensure accuracy. The architecture employed modular design principles, a web-based interface for multi-device accessibility, and security measures such as encrypted storage and role-based access control. Functional testing, integration testing, and user acceptance trials validated system performance and reliability.Result: The implemented HMS successfully automated core hostel processes improved real-time data access, and significantly reduced manual workload for administrative staff. Features such as automated room allocation, maintenance request tracking, virtual hostel viewing, and dashboard-based monitoring demonstrated high usability and operational effectiveness. User feedback indicated enhanced transparency, faster response times, and improved overall efficiency in hostel management.Conclusion: The proposed system provides a scalable, secure, and intuitive solution that modernizes hostel operations. By integrating comprehensive features within a user-friendly platform, the HMS enhances administrative productivity and student satisfaction. Its modular architecture and cloud-ready design position it for future enhancements, including AI-driven analytics, mobile integration, and predictive resource planning.
AI-BASED DECISION MAKING IN MACRO AND MICROECONOMICS: TOWARD OPTIMAL EFFICIENCY Loso Judijanto; Bahrun Thalib; Haryanto; Al-Amin
Prosiding Seminar Nasional Indonesia Vol. 1 No. 3 (2024): Prosiding Seminar Nasional Indonesia
Publisher : CV. Adiba Aisha Amira

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In the last decade, Artificial Intelligence (AI) has moved from being a futuristic concept to a critical component of economic decision-making. The use of AI has been extended to various aspects of the economy, ranging from strategic decision-making at the firm level to macroeconomic policy at the government level. This study aims to examine the impact of AI on decision-making in macro and microeconomics, and understand how optimal efficiency can be achieved through the implementation of this technology. The study conducted in this research utilizes the literature research method. The results of this study show that AI has the potential to increase economic growth due to increased productivity and operational efficiency. At the macro level, AI contributes to more accurate policy planning and efficient resource management. At the micro level, AI supports businesses in gaining competitive advantage through supply chain optimization, personalization of service offerings, and better customer data management. However, the findings also emphasize the importance of addressing ethical, privacy, and accessibility challenges to ensure that the benefits of AI are widely and equitably enjoyed.
Co-Authors Achanta, Harshitha Afifah Nur Pratiwi Afrizal Akhsin Widi Putra Al-Amin Al-Amin Aldri Frinaldi Ambar Saputri Anwar, Muhammad Rehan Baehaqi Bahrun Thalib Bambang Priyatmoko Budhi Sumboro Cahyo Nugroho, Ernes Dessyana Kardha Dhidhi Pambudi Edulakanti, Vaishnavi Fadly Fadly Hadenan Towpek Hafidh Munawir Hartati Dyah Wahyuni, Hartati Dyah Haryo Basuki Isadora Nugroho Jefri Rieski Triyanto Kolan, Helini Kristono Kristono Kristono Kristono Kurniawan, Muhammad Hafiz Loso Judijanto Lucky Mahesa Yahya Moh. Imron Rosidi Muhammad Abdul Aziz Muhammad Fadhil Mungi, Keerthana Prathama Diva Wiranata Ratna Herawati Ratna Herawati Roffi Rengga Waryatko Silvia Ekasari Siti Maesaroh Siti Nandiroh siti Nurindah Sari Somayajula, Lekhana Sugeng Widada Wahyuningsih, Hartati Dyah