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All Journal Jurnal Pengabdian Masyarakat dan Riset Pendidikan Journal Education And Islamic Studies
Balqis, Aisyah Shinta
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Religion Humanities Education Languange, Linguistic, Communication & Media Mathematics Other

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Penerapan Teaching Practic Seni Rupa pada Anak Usia Dini Octavia, Fadilla Mizratul; Balqis, Aisyah Shinta; Lestari, Juli; Seisky, Seisky; Fauza, Hilyatul; Khaira, Ummi; Deswita, Miranda; Dewi, Ayu Citra
Journal Education And Islamic Studies Vol. 2 No. 2 (2024): Journal Education And Islamic Studies
Publisher : Institut Agama Islam Sumatera Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55062//JEDIES.2024.v2i2.749/5

Abstract

This study aims to identify the role of art in early childhood learning, evaluate the effectiveness of the learning approach through play with art with the research theme "Implementation of Teaching Practice of Fine Arts in Early Childhood". This article investigates the impact of art integration in learning on the development of early childhood. The research method used is qualitative using the theory of PTK in the classroom, which focuses on art as a learning tool for early childhood in the context of learning through play. Experiments were conducted with various art media, namely: finger painting, inner and outer smearing, batik using tissue, Cotton bud, painting using cotton bud, gradation, drawing with crayons. Data were analyzed using Quasi-experimental experiments to identify the main themes related to the role of art in learning and learning through play. In the implementation of the study, it was found that the role of art in learning and the effectiveness of the learning approach through play had a significant positive impact on the development of fine motor skills, creativity, and emotional and psychological responses of children. Furthermore, the results of this study emphasize the importance of art integration in preschool education to enrich the learning experience of early childhood and support the overall growth of children.
Analisis Prediksi Nilai Akhir Mahasiswa Menggunakan Algoritma Regresi Linear Berbasis Machine Learning pada Program Studi Teknologi Informasi Universitas Bina Sarana Informatika: Penelitian Salsabila, Khalisa; Maulidia, Nahya Faulya; Hafid, Shabrina Auliya Zahra; Balqis, Aisyah Shinta; Budiawan, Imam; Desmulyati, Desmulyati
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 3 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 3 (Januari 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i3.4975

Abstract

The development of information technology in education demands a fast, objective, and data-driven academic evaluation system. Problems in higher education often involve lecturers' difficulty in monitoring and predicting student academic performance early, resulting in delayed response to declining performance. One solution that can be implemented is the use of Machine Learning. This study aims to analyze the prediction of students' final grades using a Machine Learning-based Linear Regression algorithm with attendance and assignment grades as variables. The case study was conducted on students of the Information Technology Study Program at Bina Sarana Informatika University using simulated data of 100 students, with the data divided into 80% training and 20% testing. Model evaluation used MSE, RMSE, and R². The results showed an R² value of 0.94, which means that 94% of the variation in students' final grades can be explained by attendance and assignment grades, while 6% is influenced by other factors. These findings indicate that the Linear Regression algorithm has excellent predictive performance in predicting students' final grades objectively and data-driven.
Co-Authors Ayu Citra Dewi Desmulyati, Desmulyati Deswita, Miranda Fauza, Hilyatul Hafid, Shabrina Auliya Zahra Imam Budiawan Khaira, Ummi Lestari, Juli Maulidia, Nahya Faulya Octavia, Fadilla Mizratul Salsabila, Khalisa Seisky, Seisky