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All Journal JUPE : Jurnal Pendidikan Mandala Jurnal Kridatama Sains dan Teknologi
Banung, Floriana Letni
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Social Sciences

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The Effect of Using Black Box Ai to Improve Web Programming Skills of Informatics Education Students Banung, Floriana Letni; Sogen, Maria Magdalena Beatrice; Ndao, Angelo Fransisco Daga; Tunu, Sherwin Gainell; Koa, Ayu Desita
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.v10i2.8852

Abstract

Student   often   face   challenges   or   difficulties   in   creating   attra   web   interfaces,particularly   in   understanding   code   and   finding   suitable   coding   references.   This   study   aims   to   determine   the   impact   of   using   Blackbox.AI   in   supporting   seventh-semester   students   of   the   informatics   Education   study   program   at   Universitas   Citra   Bangsa   in   enahancing   their   web   programming   skills   approach   with   data   collected   were   conducted   using   observation   sheets   to   directly   monitor   the   students’   skill   development   in   independently   completing   web   programming   projects.   The   coolected   data   were   analyzed   using   descriptive   statistics   and   significance   testing.   The   results   of   the   study   indicate   that   the   use   of   Blackbox.AI   has   a   positive   and   significant   impact   on   improving   students’   web   programming   skills.   Students   found   it   easier   to   search   for   coding   references,   produced   more   attractive   web   designs,   and   developed   better-structured   layouts.   Furthermore   ,   students   expressed   high   satisfaction   with   the   outcomes   of   their   proggramming   tasks.   Based   on   the   questionnaire   results,   the   majority   of   students   stated   that   the   use   of   Blackbox.AI   greatly   assisted   them   in   understanding   both   the   concepts   and   practices   of   web   programming.  
Analisis Pemahaman Mahasiswa Informatika dalam Menyelesaikan Rute Terpendek Menggunakan Algoritma Dijkstra dengan Graf Berbobot Jaiman, Fridolin; Fallo, Diana Yanni Ariswati; Banung, Floriana Letni
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.v7i01.1678

Abstract

The Dijkstra algorithm is one of the shortest path search methods that is widely applied in various fields of computer science, such as digital navigation systems, logistics planning, and computer network optimization. In the context of informatics education, these algorithms are taught to reinforce programming logic and understanding of the structure of weighted graphs. However, the implementation of learning in higher education still faces various challenges, especially the understanding of informatic education students in solving the shortest path problems using the Dijkstra algorithm, as well as developing a learning approach based on case studies ans simulation. The method used is aused is a deskriptive qualitative approcah with data collection techniques in the form of learning obsevations, analysis of student assignment documents, and open questionnaires. The results showed that most students understood the process of initialization and tracing the minimum weight, but encountered difficulties in selecting the next node and tracking the shortest path. Case studies of weighted graphs and manual visualizations have been shown to help students understand and help students understand algorithmic processes more thoroughly. These findings show that real-life case-based learning models and manual simulations are able to improve students’ analytical skills and understanding of the working mechanisms of the Dijkstra algorithm.
Co-Authors Fallo, Diana Yanni Ariswati Jaiman, Fridolin Koa, Ayu Desita Ndao, Angelo Fransisco Daga Sogen, Maria Magdalena Beatrice Tunu, Sherwin Gainell