Muhammad Irfan Luthfi - Nisa Dwi Septiyanti.pdf
Creators: name: Luthfi, Muhammad Irfan
name: Septiyanti, Nisa Dwi
Publisher: name: figshare
Year: 2023
Subjects: classificationCode: 460208
subject: Natural language processing
classificationCode: 460299
subject: Artificial intelligence not elsewhere classified
classificationCode: 460105
subject: Applications in social sciences and education
classificationCode: 460106
subject: Spatial data and applications
classificationCode: 460199
subject: Applied computing not elsewhere classified
classificationCode: 460906
subject: Information systems education
classificationCode: 461204
subject: Programming languages
classificationCode: 461206
subject: Software architecture
classificationCode: 461207
subject: Software quality, processes and metrics
classificationCode: 461208
subject: Software testing, verification and validation
classificationCode: 461299
subject: Software engineering not elsewhere classified

description: This research aims to develop a prototype of an intelligent final project assistant that uses GPT (Generative Pre-trained Transformer) technology as a tool for students to complete their final projects. This is a research project with the primary goal of creating a tool that can assist students in navigating and improving the quality of their final projects.The prototype focuses on several key functions, including:Final Project Content Analysis: The prototype is capable of analyzing the content of students' final projects. This may include identifying the topic, assessing the structure, and understanding the content of the final project.Feedback Provision: The prototype provides feedback to students based on the analysis of the content of their final projects. This feedback may relate to the strengths and weaknesses of the final project and can help students understand areas that need improvement.Providing Recommendations: The prototype can also provide relevant and tailored recommendations to meet the needs of the supervisors. These recommendations aim to enhance the quality of the students' final projects.The research involves various stages of prototype development and internal testing. Prototype testing includes evaluating basic functionality, interface interactivity, and performance in providing recommendations and feedback. The results of these internal tests are used as a basis for improvement and enhancement in the development of this prototype.The research findings indicate that this final project assistant prototype has the potential to provide significant benefits to students in the process of completing their final projects. With its content analysis and feedback capabilities, the prototype can help students understand the strengths and weaknesses of their final projects. Furthermore, the provision of relevant recommendations based on the needs of supervisors can improve the final quality of those projects.This research is considered an initial step in the development of an intelligent tool to support students in navigating the complexity of their final projects. Further development and integration with input from students and supervisors are expected to strengthen the role of this prototype as a valuable tool in higher education.In the context of this research, the researchers are focused on using GPT technology to create a final project assistant that can enhance students' academic experiences and outcomes in completing their final projects.