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All Journal Community Engagement and Emergence Journal (CEEJ) Jurnal Pendidikan Teknologi Informasi dan Komunikasi
Sintaria Sembiring
Indonesian Adventist University
Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Health Professions Other

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Rethinking ICT Integration in Indonesian Schools: The Role of Digital Self-Learning Beyond Institutional Support Henry Pandia; Sintaria Sembiring
JENTIK : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Vol. 5 No. 1 (2026): Forthcoming Issue
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/8xzx9j47

Abstract

Purpose of the Study: This study examines the relationships among Digital Self-Learning (DSL), Institutional Support (IS), Professional Development (PD), and Technology Integration (TI) among Indonesian teachers. Specifically, the study investigates how teachers' autonomous digital learning behavior contributes to classroom-level ICT integration beyond formal institutional and training mechanisms.Methodology: A quantitative cross-sectional survey was conducted involving 221 Indonesian in-service teachers. The study applied Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the data, examine relations among the proposed constructs, and explore the mechanisms underlying technology integration.Main Findings: Digital Self-Learning is the strongest predictor of both Professional Development and Technology Integration. Institutional Support significantly influences Digital Self-Learning but does not directly affect Technology Integration, suggesting that institutional conditions primarily contribute through enabling teachers' self-directed learning behavior. Professional Development further strengthens Technology Integration, whereas demographic variables such as age, gender, and educational level exert little influence. Although the proposed model confirmed substantial explanatory power, its out-of-sample projecting performance was limited. Therefore, the findings should be interpreted primarily from an explanatory rather than a predictive perspective.Novelty/Originality of this Study: The novelty of this study lies in its reconceptualization of ICT integration as a behaviorally driven process in which Digital Self-Learning functions as the central mechanism linking institutional conditions, professional growth, and classroom technology integration. The findings contribute to the growing discourse on teacher digital capability and offer practical insights for developing more adaptive and sustainable ICT integration strategies in educational settings.
Penerapan Metode Naive Bayes Untuk Klarifikasi Keluhan Pengguna Aplikasi MyTelkomsel Glori Yani Hutabarat; Sintaria Sembiring
Community Engagement and Emergence Journal (CEEJ) Vol. 6 No. 5 (2025): Community Engagement & Emergence Journal (CEEJ)
Publisher : Yayasan Riset dan Pengembangan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/ceej.v6i6.9494

Abstract

Menganalisis keluhan pengguna terhadap aplikasi MyTelkomsel dengan menggunakan metode Naive Bayes sebagai model klasifikasi teks adalah tujuan utama dari penelitian ini. Data yang digunakan berupa 800 ulasan negatif yang kumpulkan dari Google Play Store pada periode 1 Mei hingga 1 September 2025. Proses pengolahan data dilakukan dengan beberapa tahap, yaitu pembersihan data (cleaning), case folding, normalisasi, stopword removal, tokenisasi, dan stemming. Setelah itu, data direpresentasikan menggunakan metode TF-IDF dan diberi label secara manual berdasarkan isi keluhan yang terkandung dalam ulasan pengguna. Hasil pengujian menunjukkan bahwa algoritma Naïve Bayes mampu melakukan klasifikasi keluhan pengguna dengan akurasi sebesar 78%, precision 54,5%, recall 71,4%, dan F1-score 61,8%. Berdasarkan hasil klasifikasi, kategori masalah layanan menjadi keluhan paling dominan dengan persentase sebesar 36,25%, diikuti oleh kategori harga paket mahal (17,25%) dan fitur aplikasi (9,50%). Hasil ini menunjukkan bahwa sebagian besar pengguna mengalami kendala pada koneksi jaringan, kestabilan aplikasi, serta harga paket yang dinilai terlalu tinggi. Dapat disimpulkan bahwa metode Naïve Bayes efektif digunakan untuk mengidentifikasi dan mengelompokkan keluhan pengguna aplikasi MyTelkomsel. Temuan penelitian ini diharapkan dapat membantu pengembang aplikasi dan pihak Telkomsel dalam memahami fokus utama permasalahan pengguna serta menjadi dasar dalam peningkatan kualitas layanan dan kepuasan pelanggan.
Co-Authors Glori Yani Hutabarat Henry Pandia