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Journal : International Transactions on Artificial Intelligence (ITALIC)

Design and Implementation of a Relational Database for an Academic Information System Azuddin, Muna; Yusup, Muhamad; Setiyowati, Harlis; Wibowo, Shesilia; Suwita, Jaka; Basuki, Sucipto; Astuti, Eka Dian
International Transactions on Artificial Intelligence Vol. 3 No. 2 (2025): May
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v3i2.801

Abstract

This paper focuses on the design and implementation of a relational database for an Academic Information System (AIS), aiming to streamline data management and improve the efficiency of academic processes. The study highlights challenges faced by educational institutions in managing large volumes of student and academic data, often resulting in inefficiencies and errors. The objective is to create a relational database supporting student information, course registrations, faculty assignments, and academic records. The methodology includes developing an Entity-Relationship (ER) model, applying database normalization, and implementing the system using Structured Query Language (SQL). The result is a functional database that improves data retrieval speed, enhances integrity, and simplifies access for academic staff and administrators. The solution contributes to optimizing academic data management by ensuring consistency, reducing errors, and offering scalability for future growth. This research also includes system performance evaluations and stakeholder feedback from faculty, staff, and students. Findings reveal significant improvements in usability, accuracy, and system responsiveness compared to prior legacy systems. Integrated security measures, including role-based access and encryption, safeguard data and ensure compliance with institutional privacy policies. The relational database framework supports real-time access, centralized control, and efficient administrative workflows. Overall, this system strengthens digital infrastructure in educational institutions and aligns with broader digital transformation goals. It enhances data-driven decision-making and supports sustainable, scalable, and secure academic information management, making it a valuable contribution to improving operational performance and educational service delivery in higher education settings.
Integrating MidJourney Scripts into Architectural Design for Aesthetic Innovation Aini, Qurotul; Setiyowati, Harlis; Ikhsan, Ramiro Santiago; Amroni, Amroni; Pasha, Lukita
International Transactions on Artificial Intelligence Vol. 4 No. 1 (2025): November
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v4i1.955

Abstract

The use of Artificial Intelligence (AI) in creative disciplines, particularly architecture, has introduced a paradigm shift in how design concepts are developed and visualized. This research explores the integration of MidJourney generative scripts within the architectural design process. Using a hybrid methodology of qualitative observation and computational experimentation, this study evaluates how AI-driven image generation influences form exploration, material perception, and aesthetic decision-making. The main objective is to identify how AI-based generative systems, specifically MidJourney, can enhance conceptual creativity and accelerate the design iteration cycle in architectural practice. Unlike previous procedural models limited to parametric control, this study introduces an adaptive AI human feedback mechanism enabling continuous co-evolution between designer intent and machine generation. Our findings indicate that AI-assisted workflows enhance the production of innovative architectural compositions, offering greater visual diversity, while simultaneously enhancing creative efficiency and reducing design fatigue. Quantitatively, AI integration improved design iteration speed by 65% and increased aesthetic consistency scores from 78% to 91%, compared to traditional workflows. Integrating MidJourney generative scripting into architectural workflows creates a dynamic feedback loop between human intuition and machine creativity, leading to a new model of aesthetic co-creation that expands the boundaries of contemporary architectural design.