Dian Atmasani
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Evaluasi Kemampuan Profesional Mahasiswa Calon Guru Informatika Melalui Praktik Pengalaman Lapangan Maya Sari Wahyuni; Muh. Isbar Pratama; Nurul Mukhlisah Abdal; Dian Atmasani
Information Technology Education Journal Vol. 3, No. 3, September (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

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Abstract

Penelitian ini bertujuan untuk mengevaluasi kemampuan profesional mahasiswa calon guru informatika melalui Praktik Pengalaman Lapangan (PPL). Masalah yang ingin diselesaikan adalah bagaimana hasil kemampuan profesional mahasiswa setelah mengikuti PPL, dengan fokus pada empat aspek utama: perencanaan pembelajaran, pelaksanaan pembelajaran, evaluasi pembelajaran, dan sikap profesionalisme. Penelitian ini menggunakan pendekatan kuantitatif deskriptif dengan metode survei. Data dikumpulkan melalui kuesioner yang disebarkan kepada 50 mahasiswa dari total populasi 200 mahasiswa PPG Prajabatan Program Studi Informatika di Universitas Negeri Makassar. Hasil penelitian menunjukkan bahwa kemampuan mahasiswa dalam perencanaan pembelajaran, pelaksanaan pembelajaran, dan evaluasi pembelajaran berada dalam kategori baik, dengan skor rata-rata masing-masing 4.28, 4.12, dan 4.14. Aspek sikap profesionalisme mencatatkan skor tertinggi dengan rata-rata 4.54, menunjukkan komitmen tinggi mahasiswa dalam menjaga etika profesional. Berdasarkan hasil tersebut, dapat disimpulkan bahwa secara keseluruhan, mahasiswa telah menunjukkan kompetensi yang baik dalam aspek-aspek tersebut, namun perlu penguatan dalam pemanfaatan teknologi dalam pembelajaran dan evaluasi berbasis kompetensi. Penelitian ini diharapkan dapat memberikan kontribusi terhadap pengembangan kurikulum dan peningkatan kualitas pendidikan calon guru informatika di Indonesia.
HUBUNGAN HASIL BELAJAR MATA PELAJARAN MATEMATIKA DAN FISIKA DENGAN PENGETAHUAN SISWA PADA MATA PELAJARAN PEMPROGRAMAN DASAR DI SMK NEGERI 7 TAKALAR Dian Atmasani; Muhammad Yahya; Muhammad Farid
UNM Journal of Technology and Vocational Volume 5, Issue 3, Oktober (2021)
Publisher : Program Studi S2 Pendidikan Teknologi dan Kejuruan

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Abstract

This study aims to determine the description of student learning outcomes in Mathematics, Physics and Basic Programming subjects at SMK Negeri 7 Takalar and to determine the relationship between student learning outcomes in Mathematics and Physics subjects with Student Knowledge in Basic Programming subjects. Ex-post facto research method. The total population is 210 people and the sample is 63 people taken at random proportionally. Data collection using documentation and tests. Hypothesis testing is carried out after conducting the analysis prerequisite test. The results of this study indicate that: (1) student learning outcomes in Mathematics are in the "good" criteria. (2) student learning outcomes in Physics subjects are in the "good" criteria. (3) student learning outcomes in Basic Programming subjects are in the "good" criteria. (4) there is a relationship between learning outcomes in Mathematics with students' knowledge of Basic Programming subjects of R=0.418 and the value of Sig. of 0.000 < 0.05 with a contribution of 17.5%, (5) there is a relationship between learning outcomes in Physics subjects with student knowledge in Basic Programming subjects of R = 0.468 and the value of Sig. of 0.000 < 0.05 with a contribution of 21.9%, (6) there is a joint relationship with students' knowledge of Basic Programming subjects of R = 0.538 and the value of Sig. of 0.000 < 0.05 with a contribution of 28.9%. So the research hypothesis is accepted.
Artificial Intelligence in Higher Education: A Systematic Review of Its Impact on Student Learning Nurfauziah; Dian Atmasani; A. Muzawwirah Patawari; Nur Athiyyah Fadhilah; Husna Saleh
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.v4i2.8311

Abstract

The development of digital technology has made artificial intelligence an integral part of higher education. While its use by university students provides many benefits in supporting academic activities, there are also concerns about its negative impact, especially in relation to academic integrity, dependability, and critical thinking skills. This research aims to identify the positive and negative impacts of the use of artificial intelligence by university students as well as the challenges faced in the context of higher education. The method used was Systematic Literature Review with the PRISMA approach. The total population of articles obtained was 200 articles. Scientific articles were sourced from the Scopus database published between 2022 and 2025. Articles were screened based on inclusion and exclusion criteria and assessed using the CASP (Critical Appraisal Skills Programme) approach, resulting in 19 articles that could be analysed. The results showed that artificial intelligence can improve learning efficiency, strengthen concept understanding, and support student creativity and problem solving. However, there are serious risks such as plagiarism, dissemination of inaccurate information, and decreased motivation to learn independently. Lack of regulation and digital literacy are factors that exacerbate these negative impacts. Therefore, it is important for higher education institutions to urgently create policies for the ethical use of artificial intelligence and provide comprehensive digital literacy training to students. This research provides a scientific basis for policy makers to optimise the benefits of artificial intelligence while mitigating the risks of its use in academia.