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PERAN MACHINE LEARNING DALAM PENINGKATAN PENDIDIKAN INKLUSIF: TINJAUAN LITERATUR Yadi
Jurnal Informatika Vol. 1 No. 02 (2024): Jurnal Informatika (Juri)
Publisher : Al Ihsan Smart Cendekia

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Abstract

Pendidikan inklusif bertujuan untuk menyediakan lingkungan belajar yang setara dan mendukung bagi semua siswa, termasuk mereka yang memiliki kebutuhan khusus. Dalam beberapa tahun terakhir, machine learning (ML) telah menjadi salah satu teknologi yang menawarkan solusi inovatif untuk meningkatkan kualitas pendidikan inklusif. Kajian ini bertujuan untuk meninjau peran machine learning dalam pendidikan inklusif melalui analisis sistematis literatur yang diterbitkan selama lima tahun terakhir. Metodologi Systematic Literature Review (SLR) diterapkan untuk mengidentifikasi, mengevaluasi, dan menyintesis temuan dari berbagai studi terkait. Hasil kajian menunjukkan bahwa algoritma ML seperti decision tree, support vector machine, dan neural networks digunakan secara luas untuk mendeteksi kebutuhan siswa, personalisasi pembelajaran, serta meningkatkan aksesibilitas dan hasil belajar. Namun, tantangan seperti bias algoritmik, kurangnya data berkualitas, dan hambatan implementasi masih memerlukan perhatian lebih lanjut. Kajian ini memberikan wawasan tentang peluang dan tantangan penggunaan machine learning dalam mendukung pendidikan inklusif dan menawarkan rekomendasi untuk penelitian dan pengembangan di masa depan.
Integrative Learning Models For Numeracy Literacy And Character Development: Insights From A Bibliometric Analysis Yulindaria, Lia; Yadi; Encep; Asep
IJORER : International Journal of Recent Educational Research Vol. 6 No. 3 (2025): May
Publisher : Faculty of Teacher Training and Education Muhammadiyah University of Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46245/ijorer.v6i3.861

Abstract

Objective: This research aims to map global trends in integrative learning models that combine numeracy literacy and character development, to provide in-depth insight into the contributions of existing research and the gaps that need to be addressed. Method: The method used is quantitative-based bibliometric analysis, with data collected from the Scopus database in the time period 2002–2024. Analysis was carried out using VOSviewer and R-Studio software to identify publication patterns, collaboration networks between authors and institutions, and dominant research themes. Results: The research results show a significant increase in related publications since 2016, with a peak in research activity in 2024. The main findings indicate that the topics of numeracy literacy and character development are increasingly gaining global attention, with the largest contributions coming from the fields of social sciences, computer science, and education. Co-occurrence analysis reveals that terms such as "e-learning," "digital literacy," and "project-based learning" are the main focus in the integration of numeracy literacy and character development. Novelty: The implication of this research is the need to develop evidence-based integrative learning models that can be adapted contextually to improve student learning outcomes holistically.