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All Journal Jurnal Pendidikan dan Teknologi Indonesia Jurnal Pendidikan Sosial dan Konseling
Sofa, Nur
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Arts Education Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Meningkatkan Aktivitas Dan Hasil Belajar Siswa Muatan IPA Materi Siklus Air Dengan Menggunakan Model Pembelajaran Program Di Kelas V SDN 5 Guntung Manggis Sofa, Nur; Saleh, Muhammad
Jurnal Pendidikan Sosial Dan Konseling Vol. 1 No. 3 (2023): Oktober - Desember
Publisher : CV. ITTC INDONESIA

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Abstract

The problem in this study is the low student learning activity which has an impact on student learning outcomes in learning Water Cycle Science material. The purpose of this study is to analyze teacher activities, analyze student activities, and analyze student learning outcomes. This study used a qualitative research approach with a type of classroom action research conducted in 4 meetings. The subjects of this study were grade V students of SDN 5 Guntung Manggis, the number of students was 28 students consisting of 10 male students and 18 female students. The types of data in this study are qualitative data and quantitative data. Qualitative data are obtained through observation of teacher and student activities. In addition, quantitative data is obtained through student learning outcomes. Then the results of the research obtained explained that teacher activities at meeting IV obtained "very good" criteria. Student activity at the IV meeting has reached 100% with the criterion of "very active". The classical completeness of student learning outcomes at Meeting IV has also received 100%. Furthermore, the conclusion reached in this study is that applying the PROGRAM model which is a combination of PBL, NHT, and Make a Match models can improve student activity and learning outcomes for students.
Eksplorasi Model Hybrid Transformer-Latent Semantic Analysis (LSA) Untuk Pemahaman Konteks Teks Berita Berbahasa Indonesia Sofa, Nur; Utomo, Fandy Setyo; Saputro, Rujianto Eko
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 5 (2025): JPTI - Mei 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.662

Abstract

Kemajuan teknologi informasi meningkatkan konsumsi berita digital, menuntut sistem Natural Language Processing (NLP) yang efisien dalam memahami bahasa Indonesia. Namun, kompleksitas morfologi bahasa Indonesia menyulitkan model NLP konvensional dalam menangkap makna semantik secara akurat. Model deep learning seperti Transformer unggul dalam menangkap hubungan semantik lokal, sementara Latent Semantic Analysis  (LSA) memahami hubungan semantik global melalui reduksi dimensi. Namun, Transformer membutuhkan sumber daya komputasi besar, sedangkan LSA cenderung kehilangan konteks sintaksis. Penelitian ini mengusulkan model hybrid yang mengintegrasikan Transformer dan LSA untuk meningkatkan pemahaman teks berita Indonesia serta mengevaluasi performanya dibandingkan model individu dan deep learning yang lebih kompleks. Evaluasi menggunakan Accuracy, F1-Score, BLEU Score, ROUGE, dan Perplexity. Model hybrid mencapai akurasi 0.510760 dan F1-Score 0.520486, lebih baik dari LSA dan Transformer, tetapi masih tertinggal dari BERT dan GPT. Meski demikian, model hybrid lebih efisien secara komputasi dibandingkan model deep learning yang lebih kompleks. Penelitian ini berkontribusi pada pengembangan NLP bahasa Indonesia dengan pendekatan yang lebih ringan. Implikasi penelitian menunjukkan perlunya dataset lebih besar dan teknik embedding lebih maju. Penelitian selanjutnya dapat mengeksplorasi integrasi model hybrid dengan BERT atau GPT, serta teknik embedding lain seperti word2vec atau fastText untuk meningkatkan pemahaman semantik.
Co-Authors Fandy Setyo Utomo Muhammad Saleh Rujianto Eko Saputro