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All Journal JUPE : Jurnal Pendidikan Mandala Jurnal Kridatama Sains dan Teknologi
Do'o, Faldi
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Social Sciences

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Analysis of the Utilization of AI ChatGPT in Assisting the Learning Process of Informatics Education Students at Citra Bangsa University Hendrik, Felsita Natalia; Sogen, Maria Magdalena Beatrice; Baidenggan, Wulan Marsela; Do'o, Faldi
JUPE : Jurnal Pendidikan Mandala Vol 10, No 2 (2025): JUPE : Jurnal Pendidikan Mandala (Juni)
Publisher : Lembaga Penelitian dan Pendidikan Mandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58258/jupe.v10i2.8860

Abstract

This study aims to analyze the utilization of Artificial Intelligence (AI) technology, specifically ChatGPT, in assisting the learning process of students in the Informatics Education study program. The research focuses on the following issues: the level of ChatGPT utilization by students during their learning activities; the benefits experienced from using ChatGPT as a tool to understand material, debug code, and complete assignments; and students’ perceptions of the effectiveness of ChatGPT in enhancing their understanding of Informatics coursework.The method used in this study refers to a quantitative approach with a survey method, employing data collection through the distribution of structured questionnaire instruments to research participants, namely active students of the Informatics Education Study Program. Out of 30 respondents, 96.7% use ChatGPT, primarily to understand material, complete assignments, and engage in independent learning. Students identified various functional benefits from using ChatGPT, such as increased study time efficiency, ease in obtaining conceptual clarifications, and the ability to access explanations that are more structured and easier to understand compared to conventional sourcesFurthermore, most students gave positive evaluations of ChatGPT as a digital entity capable of increasing learning motivation, improving material comprehension, saving time, and supporting practical tasks. These findings confirm ChatGPT’s potential as an effective learning support tool. However, its integration needs to be conducted wisely to avoid cognitive dependency and maintain academic integrity.Based on the overall findings presented, this study recommends that the use of ChatGPT in higher education contexts be done proportionally, prudently, and accompanied by a critical attitude. Students are encouraged not to passively accept every piece of information provided by the AI system but rather to use it as an intellectual stimulus to explore further knowledge, develop deeper understanding, and uphold academic integrity in every learning process.  
Optimasi Jalur Terpendek Menggunakan Algoritma Dijkstra dan Greedy pada Sistem Informasi Geografis Taneo, Rizaldy E; Ndun, Riandri; Diana Y.A.; Do'o, Faldi
Jurnal Kridatama Sains dan Teknologi Vol 7 No 01 (2025): Jurnal Kridatama Sains dan Teknologi
Publisher : Universitas Ma'arif Nahdlatul Ulama Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53863/kst.v7i01.1664

Abstract

The shortest path search is a primary challenge in the development of Geographic Information Systems (GIS), especially for navigation, logistics, and regional planning applications. This study discusses the optimization of the shortest path by comparing two popular algorithms, Dijkstra and Greedy Best-First Search (Greedy BFS), on a weighted graph representing a road network. The research was conducted experimentally by constructing a fictitious graph consisting of 10 nodes and 15 edges, where each edge has a weight representing the distance between locations. Both algorithms were implemented using the Python programming language and the networkx library. Experimental results show that the Dijkstra algorithm consistently produces the optimal shortest path with the minimum total distance, although it requires longer execution time. In contrast, the Greedy BFS algorithm can find solutions more quickly, but the resulting path is not always optimal, depending on the quality of the heuristic used. In the case study, Dijkstra produced a path with a total distance of 14 km, while Greedy BFS produced a path of 17 km with shorter execution time. The visualization of results clarifies the decision differences at branching nodes between the two algorithms. This study concludes that the choice of algorithm in GIS should be adjusted to the application's needs; Dijkstra is recommended for applications requiring high accuracy, while Greedy BFS is more suitable for applications needing fast response. The results of this research are expected to serve as a reference in the development of GIS based on shortest path optimization
Co-Authors Baidenggan, Wulan Marsela Diana Y.A. Hendrik, Felsita Natalia Ndun, Riandri Sogen, Maria Magdalena Beatrice Taneo, Rizaldy E