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All Journal JUPE : Jurnal Pendidikan Mandala Jurnal Kridatama Sains dan Teknologi
Hoar, Fenesia
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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 Use of Blackbox Ai in the Coding Process in Web Development Courses Tanggo, Karolina Viviliana; Sogen, Maria Magdalena Beatrice; Hoar, Fenesia; Bay, Febronia Krista Bene
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.v10i2.8850

Abstract

 In today's digital context, artificial intelligence-based tools such as Blackbox AI are increasingly being used by students to complete programming assignments, especially in the field of web development. Blackbox AI is one form of AI that is widely used by students. This study aims to uncover concerns about students' dependence on Blackbox AI, which is considered to have a negative impact on their ability to code (do programming) during lectures or when completing assignments. In addition, there is concern that students may experience a decline in critical thinking skills due to frequent reliance on assistance in completing each existing assignment. The purpose of this study was to evaluate the extent to which students depend on Blackbox AI and its impact on critical thinking and coding skills. The method used is a quantitative descriptive approach, with data collected through a questionnaire using a Likert scale from 30 sixth semester students in the Informatics Education Study Program, Citra Bangsa University. The results of the descriptive analysis, most students felt significant benefits from utilizing Blackbox AI with an average of 77.6%, but they also faced a dependence of 63.8% and a negative effect on understanding and independence of 57.1%. Concerns about the decline in coding skills due to reliance on AI were also quite high, reaching 48.9%. This finding highlights the importance of using Blackbox AI wisely and integrated with traditional learning, so as not to hinder the development of critical thinking skills and the basics of programming in students.  
Implementasi Algoritma Dijkstra dan Greedy dalam Penyelesaian Masalah Rute Terpendek Angul, Angelina; Fallo, Diana; Tanggo, Karolina Viviliana; Belo, Ivonia Nazario Alves; Hoar, Fenesia
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.v7i01.1654

Abstract

The shortest route problem is a classic topic in graph theory that has many applications in everyday life, such as in navigation systems, logistics distribution, and network management. Two algorithms that are often used are the Algorithm and the Greedy Algorithm. The Algorithm can find the shortest path with maximum results, but it has a fairly high time complexity, making it less effective for situations that require speed. On the other hand, the Greedy Algorithm can provide solutions quickly, but does not always produce the ideal shortest path. This study uses a systematic literature review (SLR) approach to scientific publications in 2020-2025, which aims to analyze and compare the performance of the two algorithms in depth. The results of the analysis show that the Algorithm is more appropriate for situations that prioritize optimal solutions, while the Greedy Algorithm is better at decisions that require speed. This study not only provides theoretical analysis, but also discusses its practical applications in the transportation, logistics, and network sectors, and aims to provide insight into the development of more efficient and effective systems in the future
Co-Authors Angul, Angelina Bay, Febronia Krista Bene Belo, Ivonia Nazario Alves Fallo, Diana Sogen, Maria Magdalena Beatrice Tanggo, Karolina Viviliana