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Journal : Information Technology Education Journal

Agile Development of PressAI: Enhancing Educational Efficiency through QR-Based Attendance and AI-Powered Essay Scoring Fakhri , M. Miftach; Syukur, Pramudya Asoka; Pratama, Muh Idul Akbar; Mazidan, A.M Yusran; Olivia, Alya; Rosidah
Information Technology Education Journal Vol. 3, No. 3, September (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v3i3.5092

Abstract

In learning activities, common issues such as time-consuming and manipulation-prone attendance processes, as well as subjective and inconsistent essay grading, often arise. This study aims to develop PressAI, an AI-based application that automates attendance using QR code technology and provides objective essay grading powered by the OpenAI API. The application was developed using the Agile methodology integrated within the Software Development Life Cycle (SDLC) framework, through iterative stages including planning, requirements analysis, system design, implementation, and testing. The results demonstrate that PressAI enables instant and accurate attendance recording via QR scanning, provides a seamless login experience without repeated authentication, and delivers fast and objective essay assessments. With its features, PressAI is expected to enhance efficiency and transparency in the learning process while offering opportunities for further innovative feature development.
Integrating Technology with Academic Success by Evaluating ChatGPT’s Quality Compatibility and Impact on Student Performance Irwansyah Suwahyu; Yohana Rara; Nur Syafitra Ramadhani; Rosidah; Putri Nirmala; Nurrahmah Agusnaya; Syukur, Pramudya Asoka
Information Technology Education Journal Vol. 4, No. 2, May (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v4i2.8532

Abstract

The use of artificial intelligence (AI) technology in higher education has become an important element to improve students' academic performance. ChatGPT, as one of the generative AI applications, offers speed, ease of use, and relevant responses to support students' learning activities. This study aims to analyze the relationship between overall technology quality, technology characteristics, technology task suitability, compatibility, and performance impact in using ChatGPT on students' academic performance. This study used a quantitative approach with a cross-sectional design and purposive sampling technique involving 182 active student respondents using ChatGPT. Data were collected through an online questionnaire using a 5-point Likert scale covering five main variables. The results of descriptive analysis show a mean value that illustrates that students generally have a positive perception of the use of ChatGPT in supporting their academic activities. These findings suggest that ChatGPT has great potential in improving student productivity and comprehension, although service quality, task suitability, and function compatibility need to be continuously improved to better suit academic needs. Thus, the implementation of ChatGPT in higher education needs to be planned adaptively and ethically in order to optimally support students' learning success in the digital era